50+ Machine Learning (ML) Jobs in India

🚀 Join GuppShupp: Build Bharat's First AI Lifelong Friend

GuppShupp's mission is nothing short of building Bharat's First AI Lifelong Friend. This is more than just a chatbot—it's about creating a truly personalized, consistently available companion that understands and grows with the user over a lifetime. We are pioneering this deeply personal experience using cutting-edge Generative AI.

We're hiring a Founding AI Engineer (1+ Year Experience) to join our small team of A+ builders and craft the foundational LLM and infrastructure behind this mission.

If you are passionate about:

• Deep personalization and managing complex user state/memory.
• Building high-quality, high-throughput AI tools.
• Next-level infrastructure at an incredible scale (millions of users).

What you'll do (responsibilities)

We're looking for an experienced individual contributor who enjoys working alongside other experienced engineers and iterate on AI

Prompt Engineering & Testing

• Write, test, and iterate numerous prompt variations.
• Identify and fix failures, biases, or edge cases in AI responses.

Advance LLM and Development

• Engineer solutions for long-term conversational memory and statefulness in LLMs.
• Implement techniques (e.g., retrieval-augmented generation (RAG) or summarization) to effectively manage and extend the context window for complex tasks.

Collaboration & Optimization

• Work with product and growth teams to turn feature goals into effective technical prompts.
• Optimize prompts for diverse use cases (e.g., chat, content, personalization).

LLM Fine-Tuning & Management

• Prepare, clean, and format datasets for training.
• Run fine-tuning jobs on smaller, specialized language models.
• Assist in deploying, monitoring, and maintaining these models

What we're looking for (qualifications)

You are an AI Engineer who has successfully shipped systems in this domain for over a year—you won't need ramp-up time. We prioritize continuous learning and hands-on skill development over formal qualifications. Crucially, we are looking for a teammate driven by a sense of duty to the user and a passion for taking full ownership of their contributions.

Role: Azure AI Tech Lead

Exp-3.5-7 Years

Location: Remote / Noida (NCR)

Notice Period: Immediate to 15 days

Mandatory Skills: Python, Azure AI/ML, PyTorch, TensorFlow, JAX, HuggingFace, LangChain, Kubeflow, MLflow, LLMs, RAG, MLOps, Docker, Kubernetes, Generative AI, Model Deployment, Prometheus, Grafana

JOB DESCRIPTION

As the Azure AI Tech Lead, you will serve as the principal technical expert leading the design, development, and deployment of advanced AI and ML solutions on the Microsoft Azure platform. You will guide a team of engineers, establish robust architectures, and drive end-to-end implementation of AI projects—transforming proof-of-concepts into scalable, production-ready systems.

Key Responsibilities:

• Lead architectural design and development of AI/ML solutions using Azure AI, Azure OpenAI, and Cognitive Services.
• Develop and deploy scalable AI systems with best practices in MLOps across the full model lifecycle.
• Mentor and upskill AI/ML engineers through technical reviews, training, and guidance.
• Implement advanced generative AI techniques including LLM fine-tuning, RAG systems, and diffusion models.
• Collaborate cross-functionally to translate business goals into innovative AI solutions.
• Enforce governance, responsible AI practices, and performance optimization standards.
• Stay ahead of trends in LLMs, agentic AI, and applied research to shape next-gen solutions.

Qualifications:

• Bachelor’s or Master’s in Computer Science or related field.
• 3.5–7 years of experience delivering end-to-end AI/ML solutions.
• Strong expertise in Azure AI ecosystem and production-grade model deployment.
• Deep technical understanding of ML, DL, Generative AI, and MLOps pipelines.
• Excellent analytical and problem-solving abilities; applied research or open-source contributions preferred.

We're seeking an AI/ML Engineer to join our team-

As an AI/ML Engineer, you will be responsible for designing, developing, and implementing artificial intelligence (AI) and machine learning (ML) solutions to solve real world business problems. You will work closely with cross-functional teams, including data scientists, software engineers, and product managers, to deploy and integrate Applied AI/ML solutions into the products that are being built at NonStop. Your role will involve researching cutting-edge algorithms, data processing techniques, and implementing scalable solutions to drive innovation and improve the overall user experience.

Responsibilities

• Applied AI/ML engineering; Building engineering solutions on top of the AI/ML tooling available in the industry today. Eg: Engineering APIs around OpenAI
• AI/ML Model Development: Design, develop, and implement machine learning models and algorithms that address specific business challenges, such as natural language processing, computer vision, recommendation systems, anomaly detection, etc.
• Data Preprocessing and Feature Engineering: Cleanse, preprocess, and transform raw data into suitable formats for training and testing AI/ML models. Perform feature engineering to extract relevant features from the data
• Model Training and Evaluation: Train and validate AI/ML models using diverse datasets to achieve optimal performance. Employ appropriate evaluation metrics to assess model accuracy, precision, recall, and other relevant metrics
• Data Visualization: Create clear and insightful data visualizations to aid in understanding data patterns, model behavior, and performance metrics
• Deployment and Integration: Collaborate with software engineers and DevOps teams to deploy AI/ML models into production environments and integrate them into various applications and systems
• Data Security and Privacy: Ensure compliance with data privacy regulations and implement security measures to protect sensitive information used in AI/ML processes
• Continuous Learning: Stay updated with the latest advancements in AI/ML research, tools, and technologies, and apply them to improve existing models and develop novel solutions
• Documentation: Maintain detailed documentation of the AI/ML development process, including code, models, algorithms, and methodologies for easy understanding and future reference

Requirements

• Bachelor's, Master's or PhD in Computer Science, Data Science, Machine Learning, or a related field. Advanced degrees or certifications in AI/ML are a plus
• Proven experience as an AI/ML Engineer, Data Scientist, or related role, ideally with a strong portfolio of AI/ML projects
• Proficiency in programming languages commonly used for AI/ML. Preferably Python
• Familiarity with popular AI/ML libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, etc.
• Familiarity with popular AI/ML Models such as GPT3, GPT4, Llama2, BERT etc.
• Strong understanding of machine learning algorithms, statistics, and data structures
• Experience with data preprocessing, data wrangling, and feature engineering
• Knowledge of deep learning architectures, neural networks, and transfer learning
• Familiarity with cloud platforms and services (e.g., AWS, Azure, Google Cloud) for scalable AI/ML deployment
• Solid understanding of software engineering principles and best practices for writing maintainable and scalable code
• Excellent analytical and problem-solving skills, with the ability to think critically and propose innovative solutions
• Effective communication skills to collaborate with cross-functional teams and present complex technical concepts to non-technical stakeholders

MUST-HAVES: 

• Machine Learning + Aws + (EKS OR ECS OR Kubernetes) + (Redshift AND Glue) + Sage maker
• Notice period - 0 to 15 days only 
• Hybrid work mode- 3 days office, 2 days at home

SKILLS: AWS, AWS CLOUD, AMAZON REDSHIFT, EKS

ADDITIONAL GUIDELINES:

• Interview process: - 2 Technical round + 1 Client round
• 3 days in office, Hybrid model. 

CORE RESPONSIBILITIES:

• The MLE will design, build, test, and deploy scalable machine learning systems, optimizing model accuracy and efficiency
• Model Development: Algorithms and architectures span traditional statistical methods to deep learning along with employing LLMs in modern frameworks.
• Data Preparation: Prepare, cleanse, and transform data for model training and evaluation.
• Algorithm Implementation: Implement and optimize machine learning algorithms and statistical models.
• System Integration: Integrate models into existing systems and workflows.
• Model Deployment: Deploy models to production environments and monitor performance.
• Collaboration: Work closely with data scientists, software engineers, and other stakeholders.
• Continuous Improvement: Identify areas for improvement in model performance and systems.

SKILLS:

• Programming and Software Engineering: Knowledge of software engineering best practices (version control, testing, CI/CD).
• Data Engineering: Ability to handle data pipelines, data cleaning, and feature engineering. Proficiency in SQL for data manipulation + Kafka, Chaos search logs, etc. for troubleshooting; Other tech touch points are Scylla DB (like BigTable), OpenSearch, Neo4J graph
• Model Deployment and Monitoring: MLOps Experience in deploying ML models to production environments.
• Knowledge of model monitoring and performance evaluation.

REQUIRED EXPERIENCE:

• Amazon SageMaker: Deep understanding of SageMaker's capabilities for building, training, and deploying ML models; understanding of the Sage maker pipeline with ability to analyze gaps and recommend/implement improvements
• AWS Cloud Infrastructure: Familiarity with S3, EC2, Lambda and using these services in ML workflows
• AWS data: Redshift, Glue
• Containerization and Orchestration: Understanding of Docker and Kubernetes, and their implementation within AWS (EKS, ECS)

AI based systems design and development, entire pipeline from image/ video ingest, metadata ingest, processing, encoding, transmitting.

Implementation and testing of advanced computer vision algorithms.

Dataset search, preparation, annotation, training, testing, fine tuning of vision CNN models. Multimodal AI, LLMs, hardware deployment, explainability.

Detailed analysis of results. Documentation, version control, client support, upgrades.

Experience- 6 to 8 years

Location- Bangalore

Job Description-

- Extensive experience with machine learning utilizing the latest analytical models in Python. (i.e., experience in generating data-driven insights that play a key role in rapid decision-making and driving business outcomes.)

- Extensive experience using Tableau, table design, PowerApps, Power BI, Power Automate, and cloud environments, or equivalent experience designing/implementing data analysis pipelines and visualization.

- Extensive experience using AI agent platforms. (AI = data analysis: a required skill for data analysts.)

- A statistics major or equivalent understanding of statistical analysis results interpretation.

At iDreamCareer, we’re on a mission to democratize career guidance for millions of young learners across India and beyond. Technology is at the heart of this mission — and we’re looking for an Engineering Manager who thrives in high-ownership environments, thinks with an enterprising mindset, and gets excited about solving problems that genuinely change lives.

This is not just a management role. It’s a chance to shape the product, scale the platform, influence the engineering culture, and lead a team that builds with heart and hustle.

As an Engineering Manager here, you will:

• Lead a talented team of engineers while remaining hands-on with architecture and development.
• Champion the use of AI/ML, LLM-driven features, and intelligent systems to elevate learner experience.
• Inspire a culture of high performance, clear thinking, and thoughtful engineering.
• Partner closely with product, design, and content teams to deliver delightful, meaningful user experiences.
• Bring structure, clarity, and energy to complex problem-solving.
• This role is ideal for someone who loves building, mentoring, scaling, and thinking several steps ahead.

Key Responsibilities

Technical Leadership & Ownership

• Lead end-to-end development across backend, frontend, architecture, and infrastructure in partnership with product and design teams.
• Stay hands-on with the MERN stack, Python, and AI/ML technologies, while guiding and coaching a high-performance engineering team.
• Architect, develop, and maintain distributed microservices, event-driven systems, and robust APIs on AWS.

AI/ML Engineering

• Build and deploy AI-powered features, leveraging LLMs, RAG pipelines, embeddings, vector databases, and model evaluation frameworks.
• Drive prompt engineering, retrieval optimization, and continuous refinement of AI system performance.
• Champion the adoption of modern AI coding tools and emerging AI platforms to boost team productivity.

Cloud, Data, DevOps & Scaling

• Own deployments and auto-scaling on AWS (ECS, Lambda, CloudFront, SQS, SES, ELB, S3).
• Build and optimize real-time and batch data pipelines using BigQuery and other analytics tools.
• Implement CI/CD pipelines for Dockerized applications, ensuring strong observability through Prometheus, Loki, Grafana, CloudWatch.
• Enforce best practices around security, code quality, testing, and system performance.

Collaboration & Delivery Excellence

• Partner closely with product managers, designers, and QA to deliver features with clarity, speed, and reliability.
• Drive agile rituals, ensure engineering predictability, and foster a culture of ownership, innovation, and continuous improvement

Required Skills & Experience

• 8–12 years of experience in full-stack or backend engineering with at least 5+ years leading engineering teams.
• Strong hands-on expertise in the MERN stack and modern JavaScript/TypeScript ecosystems.
• 5+ years building and scaling production-grade applications and distributed systems.
• 2+ years building and deploying AI/ML products — including training, tuning, integrating, and monitoring AI models in production.
• Practical experience with SQL, NoSQL, vector databases, embeddings, and production-grade RAG systems.
• Strong understanding of LLM prompt optimization, evaluation frameworks, and AI-driven system design.
• Hands-on with AI developer tools, automation utilities, and emerging AI productivity platforms.

Preferred Skills

• Familiarity with LLM orchestration frameworks (LangChain, LlamaIndex, etc.) and advanced tool-calling workflows.
• Experience building async workflows, schedulers, background jobs, and offline processing systems.
• Exposure to modern frontend testing frameworks, QA automation, and performance testing.

Job description

Job Title: Python Trainer (Workshop Model Freelance / Part-time)

Location: Thrissur & Ernakulam

Program Duration: 30 or 60 Hours (Workshop Model)

Job Type: Freelance / Contract

About the Role:

We are seeking an experienced and passionate Python Trainer to deliver interactive, hands-on training sessions for students under a workshop model in Thrissur and Ernakulam locations. The trainer will be responsible for engaging learners with practical examples and real-time coding exercises.

Key Responsibilities:

Conduct offline workshop-style Python training sessions (30 or 60 hours total).

Deliver interactive lectures and coding exercises focused on Python programming fundamentals and applications.

Customize the curriculum based on learners skill levels and project needs.

Guide students through mini-projects, assignments, and coding challenges.

Ensure effective knowledge transfer through practical, real-world examples.

Requirements:

Experience: 15 years of training or industry experience in Python programming.

Technical Skills: Strong knowledge of Python, including OOPs concepts, file handling, libraries (NumPy, Pandas, etc.), and basic data visualization.

Prior experience in academic or corporate training preferred.

Excellent communication and presentation skills.

Mode: Offline Workshop (Thrissur / Ernakulam)

Duration: Flexible – 30 Hours or 60 Hours Total

Organization: KGiSL Microcollege

Role: Other

Industry Type: Education / Training

Department: Other

Employment Type: Full Time, Permanent

Role Category: Other

Education

UG: Any Graduate

Key Skills

Data Science,Artificial Intelligence

Role: Other

Industry Type: Education / Training

Department: Other

Employment Type: Full Time, Permanent

Role Category: Other

Education

UG: Any Graduate

Job description

Job Title: Python Trainer (Workshop Model Freelance / Part-time)

Location: Thrissur & Ernakulam

Program Duration: 30 or 60 Hours (Workshop Model)

Job Type: Freelance / Contract

About the Role:

We are seeking an experienced and passionate Python Trainer to deliver interactive, hands-on training sessions for students under a workshop model in Thrissur and Ernakulam locations. The trainer will be responsible for engaging learners with practical examples and real-time coding exercises.

Key Responsibilities:

Conduct offline workshop-style Python training sessions (30 or 60 hours total).

Deliver interactive lectures and coding exercises focused on Python programming fundamentals and applications.

Customize the curriculum based on learners skill levels and project needs.

Guide students through mini-projects, assignments, and coding challenges.

Ensure effective knowledge transfer through practical, real-world examples.

Requirements:

Experience: 15 years of training or industry experience in Python programming.

Technical Skills: Strong knowledge of Python, including OOPs concepts, file handling, libraries (NumPy, Pandas, etc.), and basic data visualization.

Prior experience in academic or corporate training preferred.

Excellent communication and presentation skills.

Mode: Offline Workshop (Thrissur / Ernakulam)

Duration: Flexible – 30 Hours or 60 Hours Total

Organization: KGiSL Microcollege

Role: Other

Industry Type: Education / Training

Department: Other

Employment Type: Full Time, Permanent

Role Category: Other

Education

UG: Any Graduate

Key Skills

Data Science,Artificial Intelligence

Role: Other

Industry Type: Education / Training

Department: Other

Employment Type: Full Time, Permanent

Role Category: Other

Education

UG: Any Graduate

About Us

Mobileum is a leading provider of Telecom analytics solutions for roaming, core network, security, risk management, domestic and international connectivity testing, and customer intelligence.

More than 1,000 customers rely on its Active Intelligence platform, which provides advanced analytics solutions, allowing customers to connect deep network and operational intelligence with real-time actions that increase revenue, improve customer experience, and reduce costs.

Headquartered in Silicon Valley, Mobileum has global offices in Australia, Dubai, Germany, Greece, India, Portugal, Singapore and UK with global HC of over 1800+. 

Join Mobileum Team

At Mobileum we recognize that our team is the main reason for our success. What does work with us mean? Opportunities!

Role: GenAI/LLM Engineer – Domain-Specific AI Solutions (Telecom)

About the Job

We are seeking a highly skilled GenAI/LLM Engineer to design, fine-tune, and operationalize Large Language Models (LLMs) for telecom business applications. This role will be instrumental in building domain-specific GenAI solutions, including the development of domain-specific LLMs, to transform telecom operational processes, customer interactions, and internal decision-making workflows.

Roles & Responsibility:

• Build domain-specific LLMs by curating domain-relevant datasets and training/fine-tuning LLMs tailored for telecom use cases.
• Fine-tune pre-trained LLMs (e.g., GPT, Llama, Mistral) using telecom-specific datasets to improve task accuracy and relevance.
• Design and implement prompt engineering frameworks, optimize prompt construction and context strategies for telco-specific queries and processes.
• Develop Retrieval-Augmented Generation (RAG) pipelines integrated with vector databases (e.g., FAISS, Pinecone) to enhance LLM performance on internal knowledge.
• Build multi-agent LLM pipelines using orchestration tools (LangChain, LlamaIndex) to support complex telecom workflows.
• Collaborate cross-functionally with data engineers, product teams, and domain experts to translate telecom business logic into GenAI workflows.
• Conduct systematic model evaluation focused on minimizing hallucinations, improving domain-specific accuracy, and tracking performance improvements on business KPIs.
• Contribute to the development of internal reusable GenAI modules, coding standards, and best practices documentation.

Desired Profile

• Familiarity with multi-modal LLMs (text + tabular/time-series).
• Experience with OpenAI function calling, LangGraph, or agent-based orchestration.
• Exposure to telecom datasets (e.g., call records, customer tickets, network logs).
• Experience with low-latency inference optimization (e.g., quantization, distillation).

Technical skills

• Hands-on experience in fine-tuning transformer models, prompt engineering, and RAG architecture design.
• Experience delivering production-ready AI solutions in enterprise environments; telecom exposure is a plus.
• Advanced knowledge of transformer architectures, fine-tuning techniques (LoRA, PEFT, adapters), and transfer learning.
• Proficiency in Python, with significant experience using PyTorch, Hugging Face Transformers, and related NLP libraries.
• Practical expertise in prompt engineering, RAG pipelines, and LLM orchestration tools (LangChain, LlamaIndex).
• Ability to build domain-adapted LLMs, from data preparation to final model deployment.

Work Experience

7+ years of professional experience in AI/ML, with at least 2+ years of practical exposure to LLMs or GenAI deployments.

Educational Qualification

• Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Natural Language Processing, or a related field.
• Ph.D. preferred for foundational model work and advanced research focus.

We are looking for an 4-5 years of experienced AI/ML Engineer who can design, develop, and deploy scalable machine learning models and AI-driven solutions. The ideal candidate should have strong expertise in data processing, model building, and production deployment, along with solid programming and problem-solving skills.

Key Responsibilities

• Develop and deploy machine learning, deep learning, and NLP models for various business use cases.
• Build end-to-end ML pipelines including data preprocessing, feature engineering, training, evaluation, and production deployment.
• Optimize model performance and ensure scalability in production environments.
• Work closely with data scientists, product teams, and engineers to translate business requirements into AI solutions.
• Conduct data analysis to identify trends and insights.
• Implement MLOps practices for versioning, monitoring, and automating ML workflows.
• Research and evaluate new AI/ML techniques, tools, and frameworks.
• Document system architecture, model design, and development processes.

Required Skills

• Strong programming skills in Python (NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Keras).
• Hands-on experience in building and deploying ML/DL models in production.
• Good understanding of machine learning algorithms, neural networks, NLP, and computer vision.
• Experience with REST APIs, Docker, Kubernetes, and cloud platforms (AWS/GCP/Azure).
• Working knowledge of MLOps tools such as MLflow, Airflow, DVC, or Kubeflow.
• Familiarity with data pipelines and big data technologies (Spark, Hadoop) is a plus.
• Strong analytical skills and ability to work with large datasets.
• Excellent communication and problem-solving abilities.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, Machine Learning, or related fields.
• Experience in deploying models using cloud services (AWS Sagemaker, GCP Vertex AI, etc.).
• Experience in LLM fine-tuning or generative AI is an added advantage.

Role - Python Developer

Location - Ahmedabad

Experience - 1 - 2 Years

Employment Type - Full-Time

Role Overview:

We are looking for a Python-focused AI/ML Engineer to develop, train, and deploy machine learning models and AI-driven solutions. The ideal candidate should have strong Python skills and hands-on experience with ML frameworks.

Key Responsibilities:

• Build and optimize ML/DL models using Python.
• Develop data pipelines and perform data preprocessing.
• Deploy models using MLOps tools and cloud platforms.
• Collaborate with cross-functional teams to deliver AI solutions.
• Conduct model testing, tuning, and performance monitoring.

Required Skills:

• Strong proficiency in Python, NumPy, Pandas, Scikit-learn.
• Experience with TensorFlow or PyTorch.
• Understanding of ML algorithms and model evaluation.
• Familiarity with REST APIs and Git.
• Basic knowledge of cloud services (AWS/Azure/GCP).

Preferred Skills:

• Experience with NLP or Computer Vision.
• Knowledge of Docker, Kubernetes, and MLflow.

About the Company

Gruve is an innovative Software Services startup dedicated to empowering Enterprise Customers in managing their Data Life Cycle. We specialize in Cyber Security, Customer Experience, Infrastructure, and advanced technologies such as Machine Learning and Artificial Intelligence. Our mission is to assist our customers in their business strategies utilizing their data to make more intelligent decisions. As a well-funded early-stage startup, Gruve offers a dynamic environment with strong customer and partner networks.

Why Gruve

At Gruve, we foster a culture of innovation, collaboration, and continuous learning. We are committed to building a diverse and inclusive workplace where everyone can thrive and contribute their best work. If you’re passionate about technology and eager to make an impact, we’d love to hear from you.

Gruve is an equal opportunity employer. We welcome applicants from all backgrounds and thank all who apply; however, only those selected for an interview will be contacted.

Position Summary

We are seeking a highly experienced and visionary Senior Engineering Manager – Inference Services to lead and scale our team responsible for building high-performance inference systems that power cutting-edge AI/ML products. This role requires a blend of strong technical expertise, leadership skills, and product-oriented thinking to drive innovation, scalability, and reliability of our inference infrastructure.

Key Responsibilities

Leadership & Strategy

• Lead, mentor, and grow a team of engineers focused on inference platforms, services, and optimizations.
• Define the long-term vision and roadmap for inference services in alignment with product and business goals.
• Partner with cross-functional leaders in ML, Product, Data Science, and Infrastructure to deliver robust, low-latency, and scalable inference solutions.

Engineering Excellence

• Architect and oversee development of distributed, production-grade inference systems ensuring scalability, efficiency, and reliability.
• Drive adoption of best practices for model deployment, monitoring, and continuous improvement of inference pipelines.
• Ensure high availability, cost optimization, and performance tuning of inference workloads across cloud and on-prem environments.

Innovation & Delivery

• Evaluate emerging technologies, frameworks, and hardware accelerators (GPUs, TPUs, etc.) to continuously improve inference efficiency.
• Champion automation and standardization of model deployment and lifecycle management.
• Balance short-term delivery with long-term architectural evolution.

People & Culture

• Build a strong engineering culture focused on collaboration, innovation, and accountability.
• Provide coaching, feedback, and career development opportunities to team members.
• Foster a growth mindset and data-driven decision-making.

Basic Qualifications

Experience

• 12+ years of software engineering experience with at least 4–5 years in engineering leadership roles.
• Proven track record of managing high-performing teams delivering large-scale distributed systems or ML platforms.
• Experience in building and operating inference systems, ML serving platforms, or real-time data systems at scale.

Technical Expertise

• Strong understanding of machine learning model deployment, serving, and optimization (batch & real-time).
• Proficiency in cloud-native technologies (Kubernetes, Docker, microservices architecture).
• Hands-on knowledge of inference frameworks (TensorFlow Serving, Triton Inference Server, TorchServe, etc.) and hardware accelerators.
• Solid background in programming languages (Python, Java, C++ or Go) and performance optimization techniques.

Preferred Qualifications

• Experience with MLOps platforms and end-to-end ML lifecycle management.
• Prior work in high-throughput, low-latency systems (ad-tech, search, recommendations, etc.).
• Knowledge of cost optimization strategies for large-scale inference workloads.

Position: QA Engineer – Machine Learning Systems (5 - 7 years)

Location: Remote (Company in Mumbai)

Company: Big Rattle Technologies Private Limited

Immediate Joiners only.

Summary:

The QA Engineer will own quality assurance across the ML lifecycle—from raw data validation through feature engineering checks, model training/evaluation verification, batch prediction/optimization validation, and end-to-end (E2E) workflow testing. The role is hands-on with Python automation, data profiling, and pipeline test harnesses in Azure ML and Azure DevOps. Success means probably correct data, models, and outputs at production scale and cadence.

Key Responsibilities:

Test Strategy & Governance

• ○ Define an ML-specific Test Strategy covering data quality KPIs, feature consistency
• checks, model acceptance gates (metrics + guardrails), and E2E run acceptance
• (timeliness, completeness, integrity).
• ○ Establish versioned test datasets & golden baselines for repeatable regression of
• features, models, and optimizers.

Data Quality & Transformation

• Validate raw data extracts and landed data lake data: schema/contract checks, null/outlier thresholds, time-window completeness, duplicate detection, site/material coverage.
• Validate transformed/feature datasets: deterministic feature generation, leakage detection, drift vs. historical distributions, feature parity across runs (hash or statistical similarity tests).
• Implement automated data quality checks (e.g., Great Expectations/pytest + Pandas/SQL) executed in CI and AML pipelines.

Model Training & Evaluation

• Verify training inputs (splits, windowing, target leakage prevention) and hyperparameter configs per site/cluster.
• Automate metric verification (e.g., MAPE/MAE/RMSE, uplift vs. last model, stability tests) with acceptance thresholds and champion/challenger logic.
• Validate feature importance stability and sensitivity/elasticity sanity checks (price/volume monotonicity where applicable).
• Gate model registration/promotion in AML based on signed test artifacts and reproducible metrics.

Predictions, Optimization & Guardrails

• Validate batch predictions: result shapes, coverage, latency, and failure handling.
• Test model optimization outputs and enforced guardrails: detect violations and prove idempotent writes to DB.
• Verify API push to third party system (idempotency keys, retry/backoff, delivery receipts).

Pipelines & E2E

• Build pipeline test harnesses for AML pipelines (data-gen nightly, training weekly,
• prediction/optimization) including orchestrated synthetic runs and fault injection
• (missing slice, late competitor data, SB backlog).
• Run E2E tests from raw data store -> ADLS -> AML -> RDBMS -> APIM/Frontend, assert
• freshness SLOs and audit event completeness (Event Hubs -> ADLS immutable).

Automation & Tooling

• Develop Python-based automated tests (pytest) for data checks, model metrics, and API contracts; integrate with Azure DevOps (pipelines, badges, gates).
• Implement data-driven test runners (parameterized by site/material/model-version) and store signed test artifacts alongside models in AML Registry.
• Create synthetic test data generators and golden fixtures to cover edge cases (price gaps, competitor shocks, cold starts).

Reporting & Quality Ops

• Publish weekly test reports and go/no-go recommendations for promotions; maintain a defect taxonomy (data vs. model vs. serving vs. optimization).
• Contribute to SLI/SLO dashboards (prediction timeliness, queue/DLQ, push success, data drift) used for release gates.

Required Skills (hands-on experience in the following):

• Python automation (pytest, pandas, NumPy), SQL (PostgreSQL/Snowflake), and CI/CD (Azure
• DevOps) for fully automated ML QA.
• Strong grasp of ML validation: leakage checks, proper splits, metric selection
• (MAE/MAPE/RMSE), drift detection, sensitivity/elasticity sanity checks.
• Experience testing AML pipelines (pipelines/jobs/components), and message-driven integrations
• (Service Bus/Event Hubs).
• API test skills (FastAPI/OpenAPI, contract tests, Postman/pytest-httpx) + idempotency and retry
• patterns.
• Familiar with feature stores/feature engineering concepts and reproducibility.
• Solid understanding of observability (App Insights/Log Analytics) and auditability requirements.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or related field.
• 5–7+ years in QA with 3+ years focused on ML/Data systems (data pipelines + model validation).
• Certification in Azure Data or ML Engineer Associate is a plus.

Why should you join Big Rattle?

Big Rattle Technologies specializes in AI/ ML Products and Solutions as well as Mobile and Web Application Development. Our clients include Fortune 500 companies. Over the past 13 years, we have delivered multiple projects for international and Indian clients from various industries like FMCG, Banking and Finance, Automobiles, Ecommerce, etc. We also specialise in Product Development for our clients.

Big Rattle Technologies Private Limited is ISO 27001:2022 certified and CyberGRX certified.

What We Offer:

• Opportunity to work on diverse projects for Fortune 500 clients.
• Competitive salary and performance-based growth.
• Dynamic, collaborative, and growth-oriented work environment.
• Direct impact on product quality and client satisfaction.
• 5-day hybrid work week.
• Certification reimbursement.
• Healthcare coverage.

How to Apply:

Interested candidates are invited to submit their resume detailing their experience. Please detail out your work experience and the kind of projects you have worked on. Ensure you highlight your contributions and accomplishments to the projects.

Lead/Senior Data Scientist - Generative AI/LLM, Healthcare

We are seeking a highly experienced and innovative Lead or Senior Data Scientist to pioneer the application of cutting-edge Generative AI and Large Language Models (LLMs) within the dynamic healthcare and life sciences domain. This is a remote opportunity requiring a minimum of 8+ years of professional experience.

The ideal candidate will be a technical leader responsible for driving the development and deployment of next-generation AI solutions that transform complex, real-world clinical data—particularly in areas like Oncology—into actionable insights. This role focuses on enhancing operational efficiencies and improving patient access and clinical outcomes across global health ecosystems.

Core Responsibilities:

• Lead the research, design, and deployment of novel Generative AI and LLM solutions for complex problems such as automated clinical document summarization, real-world evidence (RWE) generation, and patient journey analysis.
• Architect and optimize data pipelines and ML Ops strategies to handle large, diverse, and unstructured clinical datasets, ensuring model robustness and scalability in a regulated environment.
• Serve as a subject matter expert in Generative AI/LLMs, providing technical leadership, mentoring junior data scientists, and driving best practices within the team.

Required Experience:

• 8+ years of progressive experience in Data Science, Machine Learning, or AI Engineering.
• Deep technical expertise in developing, fine-tuning, and deploying Large Language Models (LLMs) and other Generative AI models in production environments.
• Strong domain knowledge in the Healthcare or Life Sciences industry, with direct experience utilizing clinical, claims, or Real-World Evidence (RWE) data.
• Proven ability to lead complex, cross-functional projects and translate business challenges into defined AI/ML solutions.

What We’re Looking For

• 3-5 years of Data Science & ML experience in consumer internet / B2C products.
• Degree in Statistics, Computer Science, or Engineering (or certification in Data Science).
• Machine Learning wizardry: recommender systems, NLP, user profiling, image processing, anomaly detection.
• Statistical chops: finding meaningful insights in large data sets.
• Programming ninja: R, Python, SQL + hands-on with Numpy, Pandas, scikit-learn, Keras, TensorFlow (or similar).
• Visualization skills: Redshift, Tableau, Looker, or similar.
• A strong problem-solver with curiosity hardwired into your DNA.
• Brownie Points
• Experience with big data platforms: Hadoop, Spark, Hive, Pig.
• Extra love if you’ve played with BI tools like Tableau or Looker.

Domain - Credit risk / Fintech 

Roles and Responsibilities: 

1. Development, validation and monitoring of Application and Behaviour score cards

for Retail loan portfolio 

2. Improvement of collection efficiency through advanced analytics

3. Development and deployment of fraud scorecard 

4. Upsell / Cross-sell strategy implementation using analytics 

5. Create modern data pipelines and processing using AWS PAAS components (Glue,

Sagemaker studio, etc.) 

6. Deploying software using CI/CD tools such as Azure DevOps, Jenkins, etc.

7. Experience with API tools such as REST, Swagger, and Postman

8. Model deployment in AWS and management of production environment

9. Team player who can work with cross-functional teams to gather data and derive

insights 

Mandatory Technical skill set : 

1. Previous experience in scorecard development and credit risk strategy development 

2. Python and Jenkins

3. Logistic regression, Scorecard, ML and neural networks 

4. Statistical analysis and A/B testing

5. AWS Sagemaker, S3 , Ec2, Dockers 

6. REST API, Swagger and Postman

7. Excel

8. SQL 

9. Visualisation tools such as Redash / Grafana 

10. Bitbucket, Githubs and versioning tools

About Us: The Next Generation of WealthTech  

We're Cambridge Wealth, an award-winning force in mutual fund distribution and Fintech. We're not just moving money; we're redefining wealth management for everyone from retail investors to ultra-HNIs (including the NRI segment). Our brand is synonymous with excellence, backed by accolades from the BSE and top Mutual Fund houses.

If you thrive on building high-performance, scalable systems that drive real-world financial impact, you'll feel right at home. Join us in Pune to build the future of finance.

[Learn more: www.cambridgewealth.in]

The Role: Engineering Meets Team Meets Customer

We're looking for an experienced, hands-on Tech Catalyst to accelerate our product innovation. This isn't just a coding job; it's a chance to blend deep backend expertise with product strategy. You will be the engine driving rapid, data-driven product experiments, leveraging AI and Machine Learning to create smart, personalized financial solutions. You'll lead by example, mentoring a small, dedicated team and ensuring technical excellence and rapid deployment in the high-stakes financial domain.

Key Impact Areas: Ship Fast, Break Ground  

1. Backend & AI/ML Innovation  

• Rapid Prototyping: Design and execute quick, iterative experiments to validate new features and market hypotheses, moving from concept to production in days, not months.
• AI-Powered Features: Build scalable Python-based backend services that integrate AI/ML models to enhance customer profiling, portfolio recommendation, and risk analysis.
• System Architecture: Own the performance, stability, and scalability of our core fintech platform, implementing best practices in modern backend development.

2. Product Leadership & Execution  

• Agile Catalyst: Drive and optimize Agile sprints, ensuring clear technical milestones, efficient resource allocation, backlog grooming and maintaining a laser focus on preventing scope creep.
• Mentorship & Management: Provide technical guidance and mentorship to a team of developers, fostering a culture of high performance, code quality, and continuous learning.
• Domain Alignment: Translate complex financial requirements and market insights into precise, actionable technical specifications and seamless user stories.
• Problem Solver: Proactively identify and resolve technical and process bottlenecks, acting as the ultimate problem solver for the engineering and product teams.

3. Financial Domain Expertise  

• High-Value Delivery: Apply deep knowledge of the mutual fund and broader fintech landscape to inform product decisions, ensuring our solutions are compliant, competitive, and truly valuable to our clients.
• Risk & Security: Proactively architect solutions with security and financial risk management baked in from the ground up, protecting client data and assets.

Your Tech Stack & Experience  

The Must-Haves  

• Mindset: A verifiable track record as a proactive First Principle Problem Solver with an intense Passion to Ship production-ready features frequently.
• Customer Empathy: Keeps the customer's experience in mind at all times.
• Team Leadership: Experience in leading, mentoring, or managing a small development team, driving technical excellence and project delivery.
• Systems Thinker: Diagnoses and solves problems by viewing the organization as an interconnected system to anticipate broad impacts and develop holistic, strategic solutions.
• Backend Powerhouse: 2+ years of professional experience with a strong focus on backend development.
• Python Guru: Expert proficiency in Python and related frameworks (e.g., Django, Flask) for building robust, scalable APIs and services.
• AI/ML Integration: Proven ability to leverage and integrate AI/ML models into production-level applications.
• Data Driven: Expert in SQL for complex data querying, analysis, and ETL processes.
• Financial Domain Acumen:Strong, demonstrable knowledge of financial products, especially mutual funds, wealth management, and key fintech metrics.

Nice-to-Haves  

• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Familiarity with Zoho Analytics, Zoho CRM and Zoho Deluge
• Familiarity with modern data analysis tools and visualization platforms (e.g., Mixpanel, Tableau, or custom dashboard tools).
• Understanding of Mutual Fund, AIF, PMS operations

Ready to Own the Backend and Shape Finance?  

This is where your code meets the capital market. If you’re a Fintech-savvy Python expert ready to lead a team and build a scalable platform in Pune, we want to talk.

Apply now to join our award-winning, forward-thinking team.

Our High-Velocity Hiring Process:  

• You Apply & Engage: Quick application and a few insightful questions. (5 min)
• Online Tech Challenge: Prove your tech mettle. (90 min)
• People Sync: A focused call to understand if there is cultural and value alignment. (30 min)
• Deep Dive Technical Interview: Discuss architecture and projects with our senior engineers. (1 hour)
• Founder's Vision Interview: Meet the leadership and discuss your impact. (1 hour)
• Offer & Onboarding: Reference and BGV check follow the successful offer.

What are you building right now that you're most proud of?

Job Title: AI Engineer

Location: Bengaluru 

Experience: 3 Years 

Working Days: 5 Days

About the Role

We’re reimagining how enterprises interact with documents and workflows—starting with BFSI and healthcare. Our AI-first platforms are transforming credit decisioning, document intelligence, and underwriting at scale. The focus is on Intelligent Document Processing (IDP), GenAI-powered analysis, and human-in-the-loop (HITL) automation to accelerate outcomes across lending, insurance, and compliance workflows.

As an AI Engineer, you’ll be part of a high-caliber engineering team building next-gen AI systems that:

• Power robust APIs and platforms used by underwriters, credit analysts, and financial institutions.
• Build and integrate GenAI agents.
• Enable “human-in-the-loop” workflows for high-assurance decisions in real-world conditions.

Key Responsibilities

• Build and optimize ML/DL models for document understanding, classification, and summarization.
• Apply LLMs and RAG techniques for validation, search, and question-answering tasks.
• Design and maintain data pipelines for structured and unstructured inputs (PDFs, OCR text, JSON, etc.).
• Package and deploy models as REST APIs or microservices in production environments.
• Collaborate with engineering teams to integrate models into existing products and workflows.
• Continuously monitor and retrain models to ensure reliability and performance.
• Stay updated on emerging AI frameworks, architectures, and open-source tools; propose improvements to internal systems.

Required Skills & Experience

• 2–5 years of hands-on experience in AI/ML model development, fine-tuning, and building ML solutions.
• Strong Python proficiency with libraries such as NumPy, Pandas, scikit-learn, PyTorch, or TensorFlow.
• Solid understanding of transformers, embeddings, and NLP pipelines.
• Experience working with LLMs (OpenAI, Claude, Gemini, etc.) and frameworks like LangChain.
• Exposure to OCR, document parsing, and unstructured text analytics.
• Familiarity with model serving, APIs, and microservice architectures (FastAPI, Flask).
• Working knowledge of Docker, cloud environments (AWS/GCP/Azure), and CI/CD pipelines.
• Strong grasp of data preprocessing, evaluation metrics, and model validation workflows.
• Excellent problem-solving ability, structured thinking, and clean, production-ready coding practices.

IMP: Please read through before applying!

Nature of role: Full-time; On-site

Location: Thiruvanmiyur, Chennai

Responsibilities:

Build and manage automation workflows using n8n, Make (Integromat), Zapier, or custom APIs.

Integrate tools across JugaadX, WhatsApp, Shopify, Meta, Google Workspace, CRMs, and internal systems.

Develop and maintain scalable, modular automation systems with clear documentation.

Integrate and experiment with AI tools and APIs such as OpenAI, Gemini, Claude, HeyGen, Runway, etc.

Create intelligent workflows — from chatbots and lead scorers to content generators and auto-responders.

Manage cloud infrastructure (VPS, Docker, SSL, security) for automations and dashboards.

Identify repetitive tasks and convert them into reliable automated processes.

Build centralized dashboards and automated reports for teams and clients.

Stay up-to-date with the latest in AI, automation, and LLM technologies, and bring new ideas to life within Jugaad’s ecosystem.

Requirements:

Hands-on experience with n8n, Make, or Zapier (or similar tools).

Familiarity with OpenAI, Gemini, HuggingFace, ElevenLabs, HeyGen, and other AI platforms.

Working knowledge of JavaScript and basic Python for API scripting.

Strong understanding of REST APIs, webhooks, and authentication.

Experience with Docker, VPS (AWS/DigitalOcean), and server management.

Proficiency with Google Sheets, Airtable, JSON, and basic SQL.

Clear communication and documentation skills — able to explain technical systems simply.

Who You Are:

A self-starter who loves automation, optimization, and innovation.

Comfortable building end-to-end tech solutions independently.

Excited to collaborate across creative, marketing, and tech teams.

Always experimenting with new AI tools and smarter ways to work.

Obsessed with efficiency, scalability, and impact — you love saving time and getting more done with less.

What You Get:

A strategic and hands-on role at the intersection of AI, automation, and operations.

The chance to shape the tech backbone of Jugaad and influence how we work, scale, and innovate.

Freedom to experiment, build, and deploy your ideas fast.

A young, fast-moving team where your work directly drives impact and growth.

Role Overview

We are looking for a highly skilled and intellectually curious Senior Data Scientist with 7+ years of experience in applying advanced machine learning and AI techniques to solve complex business problems. The ideal candidate will have deep expertise in Classical Machine Learning, Deep Learning, Natural Language Processing (NLP), and Generative AI (GenAI), along with strong hands-on coding skills and a proven track record of delivering impactful data science solutions. This role requires a blend of technical excellence, business acumen, and collaborative mindset.

Key Responsibilities

• Design, develop, and deploy ML models using classical algorithms (e.g., regression, decision trees, ensemble methods) and deep learning architectures (CNNs, RNNs, Transformers).
• Build NLP solutions for tasks such as text classification, entity recognition, summarization, and conversational AI.
• Develop and fine-tune GenAI models for use cases like content generation, code synthesis, and personalization.
• Architect and implement Retrieval-Augmented Generation (RAG) systems for enhanced contextual AI applications.
• Collaborate with data engineers to build scalable data pipelines and feature stores.
• Perform advanced feature engineering and selection to improve model accuracy and robustness.
• Work with large-scale structured and unstructured datasets using distributed computing frameworks.
• Translate business problems into data science solutions and communicate findings to stakeholders.
• Present insights and recommendations through compelling storytelling and visualization.
• Mentor junior data scientists and contribute to internal knowledge sharing and innovation.

Required Qualifications

• 7+ years of experience in data science, machine learning, and AI.
• Strong academic background in Computer Science, Statistics, Mathematics, or related field (Master’s or PhD preferred).
• Proficiency in Python, SQL, and ML libraries (scikit-learn, TensorFlow, PyTorch, Hugging Face).
• Experience with NLP and GenAI tools (e.g., Azure AI Foundry, Azure AI studio, GPT, LLaMA, LangChain).
• Hands-on experience with Retrieval-Augmented Generation (RAG) systems and vector databases.
• Familiarity with cloud platforms (Azure preferred, AWS/GCP acceptable) and MLOps tools (MLflow, Airflow, Kubeflow).
• Solid understanding of data structures, algorithms, and software engineering principles.
• Experience with Aure, Azure Copilot Studio, Azure Cognitive Services
• Experience with Azure AI Foundry would be a strong added advantage

Preferred Skills

• Exposure to LLM fine-tuning, prompt engineering, and GenAI safety frameworks.
• Experience in domains such as finance, healthcare, retail, or enterprise SaaS.
• Contributions to open-source projects, publications, or patents in AI/ML.

Soft Skills

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder engagement abilities.
• Ability to work independently and collaboratively in cross-functional teams.
• Passion for continuous learning and innovation.

We are building an AI-powered chatbot platform and looking for an AI/ML Engineer with strong backend skills as our first technical hire. You will be responsible for developing the core chatbot engine using LLMs, creating backend APIs, and building scalable RAG pipelines.

You should be comfortable working independently, shipping fast, and turning ideas into real product features. This role is ideal for someone who loves building with modern AI tools and wants to be part of a fast-growing product from day one.

Responsibilities

• Build the core AI chatbot engine using LLMs (OpenAI, Claude, Gemini, Llama etc.)

• Develop backend services and APIs using Python (FastAPI/Flask)

• Create RAG pipelines using vector databases (Pinecone, FAISS, Chroma)

• Implement embeddings, prompt flows, and conversation logic

• Integrate chatbot with web apps, WhatsApp, CRMs and 3rd-party APIs

• Ensure system reliability, performance, and scalability

• Work directly with the founder in shaping the product and roadmap

Requirements

• Strong experience with LLMs & Generative AI

• Excellent Python skills with FastAPI/Flask

• Hands-on experience with LangChain or RAG architectures

• Vector database experience (Pinecone/FAISS/Chroma)

• Strong understanding of REST APIs and backend development

• Ability to work independently, experiment fast, and deliver clean code

Nice to Have

• Experience with cloud (AWS/GCP)

• Node.js knowledge

• LangGraph, LlamaIndex

• MLOps or deployment experience

Full Stack Engineer

Position Description

Responsibilities

• Take design mockups provided by UX/UI designers and translate them into web pages or applications using HTML and CSS. Ensure that the design is faithfully replicated in the final product.

• Develop enabling frameworks and application E2E and enhance with data analytics and AI enablement

• Ensure effective Design, Development, Validation and Support activities in line with the Customer needs, architectural requirements, and ABB Standards.

• Support ABB business units through consulting engagements.

• Develop and implement machine learning models to solve specific business problems, such as predictive analytics, classification, and recommendation systems

• Perform exploratory data analysis, clean and preprocess data, and identify trends and patterns.

• Evaluate the performance of machine learning models and fine-tune them for optimal results.

• Create informative and visually appealing data visualizations to communicate findings and insights to non-technical stakeholders.

• Conduct statistical analysis, hypothesis testing, and A/B testing to support decision-making processes.

• Define the solution, Project plan, identifying and allocation of team members, project tracking; Work with data engineers to integrate, transform, and store data from various sources.

• Collaborate with cross-functional teams, including business analysts, data engineers, and domain experts, to understand business objectives and develop data science solutions.

• Prepare clear and concise reports and documentation to communicate results and methodologies.

• Stay updated with the latest data science and machine learning trends and techniques.

• Familiarity with ML Model Deployment as REST APIs.

Background

• Engineering graduate / Masters degree with rich exposure to Data science, from a reputed institution

• Create responsive web designs that adapt to different screen sizes and devices using media queries and responsive design techniques.

• Write and maintain JavaScript code to add interactivity and dynamic functionality to web pages. This may include user input handling, form validation, and basic animations.

• Familiarity with front-end JavaScript libraries and frameworks such as React, Angular, or Vue.js. Depending on the projects, you may be responsible for working within these frameworks

• Atleast 6+ years experience in AI ML concepts, Python (preferred), prefer knowledge in deep learning frameworks like PyTorch and TensorFlow

• Domain knowledge of Manufacturing/ process Industries, Physics and first principle based analysis

• Analytical thinking for translating data into meaningful insight and could be consumed by ML Model for Training and Prediction.

• Should be able to deploy Model using Cloud services like Azure Databricks or Azure ML Studio. Familiarity with technologies like Docker, Kubernetes and MLflow is good to have.

• Agile development of customer centric prototypes or ‘Proof of Concepts’ for focused digital solutions

• Good communication skills must be able to discuss the requirements effectively with the client teams, and with internal teams.

Mission

Own architecture across web + backend, ship reliably, and establish patterns the team can scale on.

Responsibilities

• Lead system architecture for Next.js (web) and FastAPI (backend); own code quality, reviews, and release cadence.
• Build and maintain the web app (marketing, auth, dashboard) and a shared TS SDK (@revilo/contracts, @revilo/sdk).
• Integrate Stripe, Maps, analytics; enforce accessibility and performance baselines.
• Define CI/CD (GitHub Actions), containerization (Docker), env/promotions (staging → prod).
• Partner with Mobile and AI engineers on API/tool schemas and developer experience.

Requirements

• 6–10+ years; expert TypeScript, strong Python.
• Next.js (App Router), TanStack Query, shadcn/ui; FastAPI, Postgres, pydantic/SQLModel.
• Auth (OTP/JWT/OAuth), payments, caching, pagination, API versioning.
• Practical CI/CD and observability (logs/metrics/traces).

Nice-to-haves

• OpenAPI typegen (Zod), feature flags, background jobs/queues, Vercel/EAS.

Key Outcomes (ongoing)

• Stable architecture with typed contracts; <2% crash/error on web, p95 API latency in budget, reliable weekly releases.

Job Summary:

We are seeking a skilled and forward-thinking Cloud AI Professional to join our technology team. The ideal candidate will have expertise in designing, deploying, and managing artificial intelligence and machine learning solutions in cloud environments (AWS, Azure, or Google Cloud). You will work at the intersection of cloud computing and AI, helping to build scalable, secure, and high-performance AI-driven applications and services.

Key Responsibilities:

• Design, develop, and deploy AI/ML models in cloud environments (AWS, GCP, Azure).
• Build and manage end-to-end ML pipelines using cloud-native tools (e.g., SageMaker, Vertex AI, Azure ML).
• Collaborate with data scientists, engineers, and stakeholders to define AI use cases and deliver solutions.
• Automate model training, testing, and deployment using MLOps practices.
• Optimize performance and cost of AI/ML workloads in the cloud.
• Ensure security, compliance, and scalability of deployed AI services.
• Monitor model performance in production and retrain models as needed.
• Stay current with new developments in AI/ML and cloud technologies.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 3+ years of experience in AI/ML and cloud computing.
• Hands-on experience with cloud platforms (AWS, GCP, or Azure).
• Proficient in Python, TensorFlow, PyTorch, or similar frameworks.
• Strong understanding of MLOps tools and CI/CD for machine learning.
• Experience with containerization (Docker, Kubernetes).
• Familiarity with cloud-native data services (e.g., BigQuery, S3, Cosmos DB).

Preferred Qualifications:

• Certifications in Cloud (e.g., AWS Certified Machine Learning, Google Cloud Professional ML Engineer).
• Experience with generative AI, LLMs, or real-time inferencing.
• Knowledge of data governance and ethical AI practices.
• Experience with REST APIs and microservices architecture.

Soft Skills:

• Strong problem-solving and analytical skills.
• Excellent communication and collaboration abilities.
• Ability to work in a fast-paced, agile environment.

We are seeking a curious and analytical AI/ML Data Analyst to join our growing team. This role is the perfect blend of deep data analysis, statistical modeling, and applied machine learning. With 3+ years of hands-on experience, you will be responsible for translating complex business questions into data-driven solutions.

You will work cross-functionally to mine massive datasets, perform exploratory data analysis, build predictive models, and generate actionable insights that drive product strategy, operational efficiency, and business growth. The ideal candidate has a strong statistical foundation and proven experience in applying ML models to real-world business problems.

<strong>Key Responsibilities</strong>

• Exploratory Data Analysis (EDA): Query, clean, and analyze large, complex datasets to identify trends, patterns, and anomalies.
• Predictive Modeling: Develop, train, and evaluate machine learning models (e.g., regression, classification, clustering, time-series forecasting) to solve business problems like customer churn prediction, fraud detection, or sales forecasting.
• Feature Engineering: Identify and create relevant features from raw data to improve model accuracy and performance.
• Data Manipulation: Write efficient and complex SQL queries for data extraction. Use Python (Pandas, NumPy) for advanced data manipulation, cleaning, and preparation.
• Insight Generation & Communication: Translate complex statistical and ML-driven findings into clear, concise, and actionable insights for non-technical stakeholders.
• Visualization: Create compelling dashboards and reports (using tools like Tableau, Power BI, or Python libraries) to communicate model results and analytical insights.
• Model Validation: Continuously monitor and validate model performance in production, suggesting improvements and retraining as needed.
• Collaboration: Partner with data engineers, product managers, and business stakeholders to define project requirements, gather data, and deploy solutions.

Review Criteria

• Strong DevOps /Cloud Engineer Profiles
• Must have 3+ years of experience as a DevOps / Cloud Engineer
• Must have strong expertise in cloud platforms – AWS / Azure / GCP (any one or more)
• Must have strong hands-on experience in Linux administration and system management
• Must have hands-on experience with containerization and orchestration tools such as Docker and Kubernetes
• Must have experience in building and optimizing CI/CD pipelines using tools like GitHub Actions, GitLab CI, or Jenkins
• Must have hands-on experience with Infrastructure-as-Code tools such as Terraform, Ansible, or CloudFormation
• Must be proficient in scripting languages such as Python or Bash for automation
• Must have experience with monitoring and alerting tools like Prometheus, Grafana, ELK, or CloudWatch
• Top tier Product-based company (B2B Enterprise SaaS preferred)

Preferred

• Experience in multi-tenant SaaS infrastructure scaling.
• Exposure to AI/ML pipeline deployments or iPaaS / reverse ETL connectors.

Role & Responsibilities

We are seeking a DevOps Engineer to design, build, and maintain scalable, secure, and resilient infrastructure for our SaaS platform and AI-driven products. The role will focus on cloud infrastructure, CI/CD pipelines, container orchestration, monitoring, and security automation, enabling rapid and reliable software delivery.

Key Responsibilities:

• Design, implement, and manage cloud-native infrastructure (AWS/Azure/GCP).
• Build and optimize CI/CD pipelines to support rapid release cycles.
• Manage containerization & orchestration (Docker, Kubernetes).
• Own infrastructure-as-code (Terraform, Ansible, CloudFormation).
• Set up and maintain monitoring & alerting frameworks (Prometheus, Grafana, ELK, etc.).
• Drive cloud security automation (IAM, SSL, secrets management).
• Partner with engineering teams to embed DevOps into SDLC.
• Troubleshoot production issues and drive incident response.
• Support multi-tenant SaaS scaling strategies.

Ideal Candidate

• 3–6 years' experience as DevOps/Cloud Engineer in SaaS or enterprise environments.
• Strong expertise in AWS, Azure, or GCP.
• Strong expertise in LINUX Administration.
• Hands-on with Kubernetes, Docker, CI/CD tools (GitHub Actions, GitLab, Jenkins).
• Proficient in Terraform/Ansible/CloudFormation.
• Strong scripting skills (Python, Bash).
• Experience with monitoring stacks (Prometheus, Grafana, ELK, CloudWatch).
• Strong grasp of cloud security best practices.

Job Details

- Job Title: ML Engineer II - Aws, Aws Cloud

- Industry: Technology

- Domain - Information technology (IT)

- Experience Required: 6-12 years

- Employment Type: Full Time

- Job Location: Pune

- CTC Range: Best in Industry

Job Description:

Core Responsibilities:

? The MLE will design, build, test, and deploy scalable machine learning systems, optimizing model accuracy and efficiency

? Model Development: Algorithms and architectures span traditional statistical methods to deep learning along with employing LLMs in modern frameworks.

? Data Preparation: Prepare, cleanse, and transform data for model training and evaluation.

? Algorithm Implementation: Implement and optimize machine learning algorithms and statistical models.

? System Integration: Integrate models into existing systems and workflows.

? Model Deployment: Deploy models to production environments and monitor performance.

? Collaboration: Work closely with data scientists, software engineers, and other stakeholders.

? Continuous Improvement: Identify areas for improvement in model performance and systems.

Skills:

? Programming and Software Engineering: Knowledge of software engineering best practices (version control, testing, CI/CD).

? Data Engineering: Ability to handle data pipelines, data cleaning, and feature engineering. Proficiency in SQL for data manipulation + Kafka, Chaossearch logs, etc for troubleshooting; Other tech touch points are ScyllaDB (like BigTable), OpenSearch, Neo4J graph

? Model Deployment and Monitoring: MLOps Experience in deploying ML models to production environments.

? Knowledge of model monitoring and performance evaluation.

Required experience:

? Amazon SageMaker: Deep understanding of SageMaker's capabilities for building, training, and deploying ML models; understanding of the Sagemaker pipeline with ability to analyze gaps and recommend/implement improvements

? AWS Cloud Infrastructure: Familiarity with S3, EC2, Lambda and using these services in

ML workflows

? AWS data: Redshift, Glue

? Containerization and Orchestration: Understanding of Docker and Kubernetes, and their implementation within AWS (EKS, ECS)

Skills: Aws, Aws Cloud, Amazon Redshift, Eks

Must-Haves

Aws, Aws Cloud, Amazon Redshift, Eks

NP: Immediate – 30 Days

🎯 Ideal Candidate Profile:

This role requires a seasoned engineer/scientist with a strong academic background from a premier institution and significant hands-on experience in deep learning (specifically image processing) within a hardware or product manufacturing environment.

📋 Must-Have Requirements:

Experience & Education Combinations:

Candidates must meet one of the following criteria:

• Doctorate (PhD) + 2 years of related work experience
• Master's Degree + 5 years of related work experience
• Bachelor's Degree + 7 years of related work experience

Technical Skills:

• Minimum 5 years of hands-on experience in all of the following:
• Python
• Deep Learning (DL)
• Machine Learning (ML)
• Algorithm Development
• Image Processing
• 3.5 to 4 years of strong proficiency with PyTorch OR TensorFlow / Keras.

Industry & Institute:

• Education: Must be from a premier institute (IIT, IISC, IIIT, NIT, BITS) or a recognized regional tier 1 college.
• Industry: Current or past experience in a Product, Semiconductor, or Hardware Manufacturing company is mandatory.
• Preference: Candidates from engineering product companies are strongly preferred.

ℹ️ Additional Role Details:

• Interview Process: 3 technical rounds followed by 1 HR round.
• Work Model: Hybrid (requiring 3 days per week in the office).

Based on the job description you provided, here is a detailed breakdown of the Required Skills and Qualifications for this AI/ML/LLM role, formatted for clarity.

📝 Required Skills and Competencies:

💻 Programming & ML Prototyping:

• Strong Proficiency: Python, Data Structures, and Algorithms.
• Hands-on Experience: NumPy, Pandas, Scikit-learn (for ML prototyping).

🤖 Machine Learning Frameworks:

• Core Concepts: Solid understanding of:
• Supervised/Unsupervised Learning
• Regularization
• Feature Engineering
• Model Selection
• Cross-Validation
• Ensemble Methods: Experience with models like XGBoost and LightGBM.

🧠 Deep Learning Techniques:

• Frameworks: Proficiency with PyTorch OR TensorFlow / Keras.
• Architectures: Knowledge of:
• Convolutional Neural Networks (CNNs)
• Recurrent Neural Networks (RNNs)
• Long Short-Term Memory networks (LSTMs)
• Transformers
• Attention Mechanisms
• Optimization: Familiarity with optimization techniques (e.g., Adam, SGD), Dropout, and Batch Normalization.

💬 LLMs & RAG (Retrieval-Augmented Generation):

• Hugging Face: Experience with the Transformers library (tokenizers, embeddings, model fine-tuning).
• Vector Databases: Familiarity with Milvus, FAISS, Pinecone, or ElasticSearch.
• Advanced Techniques: Proficiency in:
• Prompt Engineering
• Function/Tool Calling
• JSON Schema Outputs

🛠️ Data & Tools:

• Data Management: SQL fundamentals; exposure to data wrangling and pipelines.
• Tools: Experience with Git/GitHub, Jupyter, and basic Docker.

🎓 Minimum Qualifications (Experience & Education Combinations):

Candidates must have experience building AI systems/solutions with Machine Learning, Deep Learning, and LLMs, meeting one of the following criteria:

• Doctorate (Academic) Degree + 2 years of related work experience.
• Master's Level Degree + 5 years of related work experience.
• Bachelor's Level Degree + 7 years of related work experience.

⭐ Preferred Traits and Mindset:

• Academic Foundation: Solid academic background with strong applied ML/DL exposure.
• Curiosity: Eagerness to learn cutting-edge AI and willingness to experiment.
• Communication: Clear communicator who can explain ML/LLM trade-offs simply.
• Ownership: Strong problem-solving and ownership mindset.

Job Title: AI / Machine Learning Engineer

 Company: Apprication Pvt Ltd

 Location: Goregaon East

 Employment Type: Full-time

 Experience: 2.5-4 Years

• Bachelor’s or Master’s in Computer Science, Machine Learning, Data Science, or related field.
• Proven experience of 2.5-4 years as an AI/ML Engineer, Data Scientist, or AI Application Developer.
• Strong programming skills in Python (TensorFlow, PyTorch, Scikit-learn); familiarity with LangChain, Hugging Face, OpenAI API is a plus.
• Experience in model deployment, serving, and optimization (FastAPI, Flask, Django, or Node.js).
• Proficiency with databases (SQL and NoSQL: MySQL, PostgreSQL, MongoDB).
• Hands-on experience with cloud ML services (Sage Maker, Vertex AI, Azure ML) and DevOps tools (Docker, Kubernetes, CI/CD).
• Knowledge of MLOps practices: model versioning, monitoring, retraining, experiment tracking.
• Familiarity with frontend frameworks (React.js, Angular, Vue.js) for building AI-driven interfaces (nice to have).
• Strong understanding of data structures, algorithms, APIs, and distributed systems.
• Excellent problem-solving, analytical, and communication skills.
• Develop and maintain ETL pipelines, data preprocessing workflows, and feature engineering processes.
• Ensure solutions meet security, compliance, and performance standards.
• Stay updated with the latest research and trends in deep learning, generative AI, and LLMs.

📍Company: Versatile Commerce

 📍 Position: Data Scientists

 📍 Experience: 3-9 yrs

 📍 Location: Hyderabad (WFO)

 📅 Notice Period: 0- 15 Days

Job Description:

About CoffeeBeans Consulting

CoffeeBeans is a tech-driven software consulting company that helps businesses solve complex problems using modern data, AI, and engineering solutions. We blend deep technical expertise with a product mindset to build scalable, intelligent, and high-impact solutions across industries. Our data science team works on end-to-end delivery—from exploration and modeling to GenAI application development and deployment.

Location : Bangalore / Pune 

Work mode : Hybrid ( 3 days WFO)

Role Overview

As an L2 Data Scientist, you will play a hands-on role in delivering production-grade ML and GenAI-powered applications. You are expected to independently take ownership of data science components within client projects, contribute to solutioning and design, and mentor junior team members. You will work across a range of use cases such as personalization, fraud detection, intelligent automation, RAG pipelines, and LLM-based assistants.

This role is ideal for someone who has proven experience in both traditional ML and an emerging understanding of LLMs and generative AI applications.

Key Responsibilities

ML & Data Science

Own and deliver ML model development, tuning, and evaluation for client-facing projects.

Lead exploratory data analysis, data preprocessing, and feature engineering with minimal supervision.

Build models using appropriate ML techniques (classification, regression, clustering, recommendation) and ensure performance meets business expectations.

Contribute to experimentation frameworks and model reproducibility best practices.

GenAI & LLM Applications

Design and prototype GenAI solutions using LLMs (e.g., OpenAI, Claude, Mistral, Llama).

Build RAG pipelines, prompt templates, few-shot learning prompts, and evaluation mechanisms for GenAI systems.

Integrate LLMs with APIs, vector databases (e.g., Pinecone, FAISS, Weaviate), and context providers.

Contribute to benchmarking, safety, and cost-performance trade-offs in LLM app development.

Product & Engineering Collaboration

Collaborate with engineering teams to take models from experimentation to deployment (batch/real-time).

Assist in building APIs and data pipelines needed for productionizing models.

Contribute to technical documentation, explainability reports, and client presentations.

Team & Growth

Mentor junior data scientists and review code/model design.

Stay current with advances in ML and GenAI to inform solution design and share knowledge internally.

Participate in discovery and solutioning phases with clients alongside tech leads and PMs.

Required Skills & Qualifications

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Statistics, or a related field.

4.5 - 6 years of hands-on experience in applied data science, including both ML model development and GenAI-based solutioning.

Strong command over Python and ML libraries (scikit-learn, XGBoost, LightGBM, etc.).

Experience working with LLM APIs (OpenAI, Cohere, Claude, etc.) and frameworks (LangChain, LlamaIndex, or similar).

Hands-on experience with prompt engineering, RAG workflows, and evaluating LLM outputs.

Proficiency in SQL and data wrangling tools (pandas, NumPy).

Experience working with REST APIs, Git, and cloud environments (AWS/GCP).

Good-to-Have Skills

Experience with deploying models via FastAPI, Docker, or serverless platforms.

Knowledge of MLOps tools (MLflow, DVC) and monitoring frameworks.

Experience with embeddings, vector databases, and similarity search.

What You Can Expect at CoffeeBeans

Work on real-world AI/ML problems across verticals.

Be part of a fast-moving team delivering end-to-end ML & GenAI apps.

Collaborate with experienced engineers and PMs in a flat and open culture.

Opportunities to lead, mentor, and influence tech direction.

What You’ll Be Doing:

● Own the architecture and roadmap for scalable, secure, and high-quality data pipelines

and platforms.

● Lead and mentor a team of data engineers while establishing engineering best practices,

coding standards, and governance models.

● Design and implement high-performance ETL/ELT pipelines using modern Big Data

technologies for diverse internal and external data sources.

● Drive modernization initiatives including re-architecting legacy systems to support

next-generation data products, ML workloads, and analytics use cases.

● Partner with Product, Engineering, and Business teams to translate requirements into

robust technical solutions that align with organizational priorities.

● Champion data quality, monitoring, metadata management, and observability across the

ecosystem.

● Lead initiatives to improve cost efficiency, data delivery SLAs, automation, and

infrastructure scalability.

● Provide technical leadership on data modeling, orchestration, CI/CD for data workflows,

and cloud-based architecture improvements.

Qualifications:

● Bachelor's degree in Engineering, Computer Science, or relevant field.

● 8+ years of relevant and recent experience in a Data Engineer role.

● 5+ years recent experience with Apache Spark and solid understanding of the

fundamentals.

● Deep understanding of Big Data concepts and distributed systems.

● Demonstrated ability to design, review, and optimize scalable data architectures across

ingestion.

● Strong coding skills with Scala, Python and the ability to quickly switch between them with

ease.

● Advanced working SQL knowledge and experience working with a variety of relational

databases such as Postgres and/or MySQL.

● Cloud Experience with DataBricks.

● Strong understanding of Delta Lake architecture and working with Parquet, JSON, CSV,

and similar formats.

● Experience establishing and enforcing data engineering best practices, including CI/CD

for data, orchestration and automation, and metadata management.

● Comfortable working in an Agile environment

● Machine Learning knowledge is a plus.

● Demonstrated ability to operate independently, take ownership of deliverables, and lead

technical decisions.

● Excellent written and verbal communication skills in English.

● Experience supporting and working with cross-functional teams in a dynamic

environment.

REPORTING: This position will report to Sr. Technical Manager or Director of Engineering as

assigned by Management.

EMPLOYMENT TYPE: Full-Time, Permanent

SHIFT TIMINGS: 10:00 AM - 07:00 PM IST

Role: Machine Learning Engineer

Employment Type: Permanent with VDart Digital

Work Location: Remote

Key Responsibilities:

• Design and implement machine learning workflows from data ingestion to model deployment.
• Develop, train, and fine-tune supervised and unsupervised ML models for business applications.
• Translate complex business problems into ML-based solutions and measurable outcomes.
• Build and automate model training, evaluation, and deployment pipelines.
• Collaborate with cross-functional teams to understand requirements and deliver production-grade models.
• Ensure scalability, reliability, and performance of deployed models.
• Monitor model accuracy, drift, and performance, and manage continuous improvement cycles.
• Document ML experiments, workflows, and results for reproducibility.

Required Skills & Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or related field.
• Strong hands-on experience in building and deploying ML models end-to-end.
• Expertise in machine learning algorithms, model evaluation, and workflow orchestration.
• Experience with ML frameworks such as Scikit-learn, TensorFlow, or PyTorch.
• Good understanding of MLOps practices, including CI/CD pipelines and model versioning.
• Experience in deploying ML solutions using APIs, containers, or cloud platforms (AWS, Azure, or GCP).
• Proven experience delivering real-world ML use cases such as classification, regression, forecasting, or recommendation systems.

Good to Have:

• Exposure to automation frameworks or ML pipeline tools (MLflow, Airflow, Kubeflow, etc.).
• Familiarity with data versioning and monitoring tools.
• Understanding of data governance and model lifecycle management.

Hi Shanon, As discussed we have one open req for AI role. The right skill set I am looking for is experience with RAG pipelines, Performance monitoring of prompts and tuning. Multi model RAG and agentic AI soon but not night away. Needless to say Python and the NLP lib experience is a must. Database knowledge is also essential. The developer needs to be in Morgan Stanley offices 3 days per week. BLR location is preferred, if not Mumbai is also fine. The duration is long term since we are looking to expand the use cases Please let me know if you have any questions. 

Job Title: Senior AI/ML/DL Engineer

Location: Hyderabad

Department: Artificial Intelligence/Machine Learning

Job Summary:

We are seeking a highly skilled and motivated Senior AI/ML/DL Engineer to contribute to

the development and implementation of advanced artificial intelligence, machine learning,

and deep learning solutions. The ideal candidate will have a strong technical background in

AI/ML/DL, hands-on experience in building scalable models, and a passion for solving

complex problems using data-driven approaches. This role involves working closely with

cross-functional teams to deliver innovative AI/ML solutions aligned with business objectives.

Key Responsibilities:

Technical Execution:

● Design, develop, and deploy AI/ML/DL models and algorithms to solve business

challenges.

● Stay up-to-date with the latest advancements in AI/ML/DL technologies and integrate

them into solutions.

● Implement best practices for model development, validation, and deployment.

Project Development:

● Collaborate with stakeholders to identify business opportunities and translate them

into AI/ML projects.

● Work on the end-to-end lifecycle of AI/ML projects, including data collection,

preprocessing, model training, evaluation, and deployment.

● Ensure the scalability, reliability, and performance of AI/ML solutions in production

environments.

Cross-Functional Collaboration:

● Work closely with product managers, software engineers, and domain experts to

integrate AI/ML capabilities into products and services.

● Communicate complex technical concepts to non-technical stakeholders effectively.

Research and Innovation:●

Explore new AI/ML techniques and methodologies to enhance solution capabilities.

● Prototype and experiment with novel approaches to solve challenging problems.

●Contribute to internal knowledge-sharing initiatives and documentation.

Quality Assurance & MLOps:

● Ensure the accuracy, robustness, and ethical use of AI/ML models.

● Implement monitoring and maintenance processes for deployed models to ensure long-term performance.

● Follow MLOps practices for efficient deployment and monitoring of AI/ML solutions.

Qualifications:

Education:

● Bachelors/Master’s or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field.

Experience:

● 5+ years of experience in AI/ML/DL, with a proven track record of delivering AI/ML solutions in production environments.

● Strong experience with programming languages such as Python, R, or Java.

● Proficiency in AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, Scikit-learn,Keras).

● Experience with cloud platforms (e.g., AWS, Azure, GCP) and big data technologies

(e.g., Hadoop, Spark).

● Familiarity with MLOps practices and tools for model deployment and monitoring.

Skills:

● Strong understanding of machine learning algorithms, deep learning architectures,

and statistical modeling.

● Excellent problem-solving and analytical skills.

● Strong communication and interpersonal skills.

● Ability to manage multiple projects and prioritize effectively.

Preferred Qualifications:

● Experience in natural language processing (NLP), computer vision, or reinforcement

learning.

● Knowledge of ethical AI practices and regulatory compliance.

● Publications or contributions to the AI/ML community (e.g., research papers,open-source projects).

What We Offer:

● Competitive salary and benefits package.

● Opportunities for professional development and career growth.

● A collaborative and innovative work environment.

● The chance to work on impactful projects that leverage cutting-edge AI/ML technologies.

Role: Data Scientist (Python + R Expertise)

Exp: 8 -12 Years

CTC: up to 30 LPA

Required Skills & Qualifications:

• 8–12 years of hands-on experience as a Data Scientist or in a similar analytical role.
• Strong expertise in Python and R for data analysis, modeling, and visualization.
• Proficiency in machine learning frameworks (scikit-learn, TensorFlow, PyTorch, caret, etc.).
• Strong understanding of statistical modeling, hypothesis testing, regression, and classification techniques.
• Experience with SQL and working with large-scale structured and unstructured data.
• Familiarity with cloud platforms (AWS, Azure, or GCP) and deployment practices (Docker, MLflow).
• Excellent analytical, problem-solving, and communication skills.

Preferred Skills:

• Experience with NLP, time series forecasting, or deep learning projects.
• Exposure to data visualization tools (Tableau, Power BI, or R Shiny).
• Experience working in product or data-driven organizations.
• Knowledge of MLOps and model lifecycle management is a plus.

If interested kindly share your updated resume on 82008 31681

MANDATORY:

• Super Quality Data Architect, Data Engineering Manager / Director Profile
• Must have 12+ YOE in Data Engineering roles, with at least 2+ years in a Leadership role
• Must have 7+ YOE in hands-on Tech development with Java (Highly preferred) or Python, Node.JS, GoLang
• Must have strong experience in large data technologies, tools like HDFS, YARN, Map-Reduce, Hive, Kafka, Spark, Airflow, Presto etc.
• Strong expertise in HLD and LLD, to design scalable, maintainable data architectures.
• Must have managed a team of at least 5+ Data Engineers (Read Leadership role in CV)
• Product Companies (Prefers high-scale, data-heavy companies)

PREFERRED:

• Must be from Tier - 1 Colleges, preferred IIT
• Candidates must have spent a minimum 3 yrs in each company.
• Must have recent 4+ YOE with high-growth Product startups, and should have implemented Data Engineering systems from an early stage in the Company

ROLES & RESPONSIBILITIES:

• Lead and mentor a team of data engineers, ensuring high performance and career growth.
• Architect and optimize scalable data infrastructure, ensuring high availability and reliability.
• Drive the development and implementation of data governance frameworks and best practices.
• Work closely with cross-functional teams to define and execute a data roadmap.
• Optimize data processing workflows for performance and cost efficiency.
• Ensure data security, compliance, and quality across all data platforms.
• Foster a culture of innovation and technical excellence within the data team.

IDEAL CANDIDATE:

• 10+ years of experience in software/data engineering, with at least 3+ years in a leadership role.
• Expertise in backend development with programming languages such as Java, PHP, Python, Node.JS, GoLang, JavaScript, HTML, and CSS.
• Proficiency in SQL, Python, and Scala for data processing and analytics.
• Strong understanding of cloud platforms (AWS, GCP, or Azure) and their data services.
• Strong foundation and expertise in HLD and LLD, as well as design patterns, preferably using Spring Boot or Google Guice
• Experience in big data technologies such as Spark, Hadoop, Kafka, and distributed computing frameworks.
• Hands-on experience with data warehousing solutions such as Snowflake, Redshift, or BigQuery
• Deep knowledge of data governance, security, and compliance (GDPR, SOC2, etc.).
• Experience in NoSQL databases like Redis, Cassandra, MongoDB, and TiDB.
• Familiarity with automation and DevOps tools like Jenkins, Ansible, Docker, Kubernetes, Chef, Grafana, and ELK.
• Proven ability to drive technical strategy and align it with business objectives.
• Strong leadership, communication, and stakeholder management skills.

PREFERRED QUALIFICATIONS:

• Experience in machine learning infrastructure or MLOps is a plus.
• Exposure to real-time data processing and analytics.
• Interest in data structures, algorithm analysis and design, multicore programming, and scalable architecture.
• Prior experience in a SaaS or high-growth tech company.

JOB DESCRIPTION/PREFERRED QUALIFICATIONS:

REQUIRED SKILLS/COMPETENCIES:

Programming Languages:

• Strong in Python, data structures, and algorithms.
• Hands-on with NumPy, Pandas, Scikit-learn for ML prototyping.

Machine Learning Frameworks:

• Understanding of supervised/unsupervised learning, regularization, feature engineering, model selection, cross-validation, ensemble methods (XGBoost, LightGBM).

Deep Learning Techniques:

• Proficiency with PyTorch or TensorFlow/Keras
• Knowledge of CNNs, RNNs, LSTMs, Transformers, Attention mechanisms.
• Familiarity with optimization (Adam, SGD), dropout, batch norm.

LLMs & RAG:

• Hugging Face Transformers (tokenizers, embeddings, model fine-tuning).
• Vector databases (Milvus, FAISS, Pinecone, ElasticSearch).
• Prompt engineering, function/tool calling, JSON schema outputs.

Data & Tools:

• SQL fundamentals; exposure to data wrangling and pipelines.
• Git/GitHub, Jupyter, basic Docker.

WHAT ARE WE LOOKING FOR?

• Solid academic foundation with strong applied ML/DL exposure.
• Curiosity to learn cutting-edge AI and willingness to experiment.
• Clear communicator who can explain ML/LLM trade-offs simply.
• Strong problem-solving and ownership mindset.

MINIMUM QUALIFICATIONS:

• Doctorate (Academic) Degree and 2 years related work experience; Master's Level Degree and related work experience of 5 years; Bachelor's Level Degree and related work experience of 7 years in building AI systems/solutions with Machine Learning, Deep Learning, and LLMs.

MUST-HAVES:

• Education/qualification:  Preferably from premier Institute like IIT, IISC, IIIT, NIT and BITS. Also regional tier 1 colleges.

• Doctorate (Academic) Degree and 2 years related work experience; or Master's Level Degree and related work experience of 5 years; or Bachelor's Level Degree and related work experience of 7 years

• Min 5 yrs experience in the Mandatory Skills: Python, Deep Learning, Machine Learning, Algorithm Development and Image Processing

• 3.5 to 4 yrs proficiency with PyTorch or TensorFlow/Keras

• Candidates from engineering product companies have higher chances of getting shortlisted (current company or past experience)

QUESTIONNAIRE: 

Do you have at least 5 years of experience with Python, Deep Learning, Machine Learning, Algorithm Development, and Image Processing? Please mention the skills and years of experience:

Do you have experience with PyTorch or TensorFlow / Keras?

• PyTorch
• TensorFlow / Keras
• Both

How many years of experience do you have with PyTorch or TensorFlow / Keras?

• Less than 3 years
• 3 to 3.5 years
• 3.5 to 4 years
• More than 4 years

Is the candidate willing to relocate to Chennai?

• Ready to relocate
• Based in Chennai

What type of company have you worked for in your career?

• Service-based IT company
• Product company
• Semiconductor company
• Hardware manufacturing company
• None of the above

Role: Sr. Data Scientist

Exp: 4 -8 Years

CTC: up to 28 LPA

Technical Skills:

o Strong programming skills in Python, with hands-on experience in deep learning frameworks like TensorFlow, PyTorch, or Keras.

o Familiarity with Databricks notebooks, MLflow, and Delta Lake for scalable machine learning workflows.

o Experience with MLOps best practices, including model versioning, CI/CD pipelines, and automated deployment.

o Proficiency in data preprocessing, augmentation, and handling large-scale image/video datasets.

o Solid understanding of computer vision algorithms, including CNNs, transfer learning, and transformer-based vision models (e.g., ViT).

o Exposure to natural language processing (NLP) techniques is a plus.

Cloud & Infrastructure:

o Strong expertise in Azure cloud ecosystem,

o Experience working in UNIX/Linux environments and using command-line tools for automation and scripting.

If interested kindly share your updated resume at 82008 31681

Role: Sr. Data Scientist

Exp: 4-8 Years

CTC: up to 25 LPA

Technical Skills:

● Strong programming skills in Python, with hands-on experience in deep learning frameworks like TensorFlow, PyTorch, or Keras.

● Familiarity with Databricks notebooks, MLflow, and Delta Lake for scalable machine learning workflows.

● Experience with MLOps best practices, including model versioning, CI/CD pipelines, and automated deployment.

● Proficiency in data preprocessing, augmentation, and handling large-scale image/video datasets.

● Solid understanding of computer vision algorithms, including CNNs, transfer learning, and transformer-based vision models (e.g., ViT).

● Exposure to natural language processing (NLP) techniques is a plus.

• Educational Qualifications:

• B.E./B.Tech/M.Tech/MCA in Computer Science, Electronics & Communication, Electrical Engineering, or a related field.
• A master’s degree in computer science, Artificial Intelligence, or a specialization in Deep Learning or Computer Vision is highly preferred

If interested share your resume on 82008 31681

Role: Sr. Data Scientist

Exp: 4-8 Years

CTC: up to 25 LPA

Technical Skills:

● Strong programming skills in Python, with hands-on experience in deep learning frameworks like TensorFlow, PyTorch, or Keras.

● Familiarity with Databricks notebooks, MLflow, and Delta Lake for scalable machine learning workflows.

● Experience with MLOps best practices, including model versioning, CI/CD pipelines, and automated deployment.

● Proficiency in data preprocessing, augmentation, and handling large-scale image/video datasets.

● Solid understanding of computer vision algorithms, including CNNs, transfer learning, and transformer-based vision models (e.g., ViT).

● Exposure to natural language processing (NLP) techniques is a plus.

• Educational Qualifications:

• B.E./B.Tech/M.Tech/MCA in Computer Science, Electronics & Communication, Electrical Engineering, or a related field.
• A master’s degree in computer science, Artificial Intelligence, or a specialization in Deep Learning or Computer Vision is highly preferred

JOB DESCRIPTION/PREFERRED QUALIFICATIONS:

KEY RESPONSIBILITIES: 

• Lead and mentor a team of algorithm engineers, providing guidance and support to ensure their professional growth and success. 
• Develop and maintain the infrastructure required for the deployment and execution of algorithms at scale. 
• Collaborate with data scientists, software engineers, and product managers to design and implement robust and scalable algorithmic solutions. 
• Optimize algorithm performance and resource utilization to meet business objectives.
• Stay up to date with the latest advancements in algorithm engineering and infrastructure technologies and apply them to improve our systems.
• Drive continuous improvement in development processes, tools, and methodologies. 

QUALIFICATIONS: 

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 
• Proven experience in developing computer vision and image processing algorithms and ML/DL algorithms. 
• Familiar with high performance computing, parallel programming and distributed systems.
• Strong leadership and team management skills, with a track record of successfully leading engineering teams. 
• Proficiency in programming languages such as Python, C++ and CUDA. 
• Excellent problem-solving and analytical skills. 
• Strong communication and collaboration abilities. 

PREFERRED QUALIFICATIONS: 

• Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). 
• Experience with GPU architecture and algo development toolkits like Docker, Apptainer. 

MINIMUM QUALIFICATIONS: 

• Bachelor's degree plus 8 + years of experience 
• Master's degree plus 8 + years of experience 
• Familiar with high performance computing, parallel programming and distributed systems.

MUST-HAVE SKILLS: 

• Phd with 6 yrs industry exp or M.Tech + 8 yrs experience or B.Tech + 10 yrs experience.
• 14 yrs exp if an IC role.
• Minimum 1 yrs experience working as a Manager/Lead
• 8 years' experience in any of the programming languages such as Python/C++/CUDA.
• 8 years' experience in Machine learning, Artificial intelligence, Deep learning.
• 2 to 3 years exp in Image processing & Computer vision is a MUST
• Product / Semi-conductor / Hardware Manufacturing company experience is a MUST. Candidates should be from engineering product companies 
• Candidates from Tier 1 colleges like (IIT, IIIT, VIT, NIT) (Preferred)
• Relocation to Chennai is mandatory

NICE TO HAVE SKILLS: 

• Candidates from Semicon or manufacturing companies
• Candidates with more than 8 CPGA

Job Title: AI / Machine Learning Engineer

 Company: Apprication Pvt Ltd

 Location: Goregaon East

 Employment Type: Full-time

 Experience: 2.5-4 Years

 About the Role

We’re seeking a highly motivated AI / Machine Learning Engineer to join our growing engineering team. You will design, build, and deploy AI-powered solutions for web and application platforms, bringing cutting-edge machine learning research into real-world production systems.

This role blends applied machine learning, backend engineering, and cloud deployment, with opportunities to work on NLP, computer vision, generative AI, and intelligent automation across diverse industries.

Key Responsibilities

• Design, train, and deploy machine learning models for NLP, computer vision, recommendation systems, and other AI-driven use cases.
• Integrate ML models into production-ready web and mobile applications, ensuring scalability and reliability.
• Collaborate with data scientists to optimize algorithms, pipelines, and inference performance.
• Build APIs and microservices for model serving, monitoring, and scaling.
• Leverage cloud platforms (AWS, Azure, GCP) for ML workflows, containerization (Docker/Kubernetes), and CI/CD pipelines.
• Implement AI-powered features such as chatbots, personalization engines, predictive analytics, or automation systems.
• Develop and maintain ETL pipelines, data preprocessing workflows, and feature engineering processes.
• Ensure solutions meet security, compliance, and performance standards.
• Stay updated with the latest research and trends in deep learning, generative AI, and LLMs.

Skills & Qualifications

• Bachelor’s or Master’s in Computer Science, Machine Learning, Data Science, or related field.
• Proven experience of 4 years as an AI/ML Engineer, Data Scientist, or AI Application Developer.
• Strong programming skills in Python (TensorFlow, PyTorch, Scikit-learn); familiarity with LangChain, Hugging Face, OpenAI API is a plus.
• Experience in model deployment, serving, and optimization (FastAPI, Flask, Django, or Node.js).
• Proficiency with databases (SQL and NoSQL: MySQL, PostgreSQL, MongoDB).
• Hands-on experience with cloud ML services (SageMaker, Vertex AI, Azure ML) and DevOps tools (Docker, Kubernetes, CI/CD).
• Knowledge of MLOps practices: model versioning, monitoring, retraining, experiment tracking.
• Familiarity with frontend frameworks (React.js, Angular, Vue.js) for building AI-driven interfaces (nice to have).
• Strong understanding of data structures, algorithms, APIs, and distributed systems.
• Excellent problem-solving, analytical, and communication skills.

Job Title: AI / Machine Learning Engineer

 Company: Apprication Pvt Ltd

 Location: Goregaon East

 Employment Type: Full-time

 Experience: 4 Years

 About the Role

We’re seeking a highly motivated AI / Machine Learning Engineer to join our growing engineering team. You will design, build, and deploy AI-powered solutions for web and application platforms, bringing cutting-edge machine learning research into real-world production systems.

This role blends applied machine learning, backend engineering, and cloud deployment, with opportunities to work on NLP, computer vision, generative AI, and intelligent automation across diverse industries.

Key Responsibilities

• Design, train, and deploy machine learning models for NLP, computer vision, recommendation systems, and other AI-driven use cases.
• Integrate ML models into production-ready web and mobile applications, ensuring scalability and reliability.
• Collaborate with data scientists to optimize algorithms, pipelines, and inference performance.
• Build APIs and microservices for model serving, monitoring, and scaling.
• Leverage cloud platforms (AWS, Azure, GCP) for ML workflows, containerization (Docker/Kubernetes), and CI/CD pipelines.
• Implement AI-powered features such as chatbots, personalization engines, predictive analytics, or automation systems.
• Develop and maintain ETL pipelines, data preprocessing workflows, and feature engineering processes.
• Ensure solutions meet security, compliance, and performance standards.
• Stay updated with the latest research and trends in deep learning, generative AI, and LLMs.

Skills & Qualifications

• Bachelor’s or Master’s in Computer Science, Machine Learning, Data Science, or related field.
• Proven experience of 4 years as an AI/ML Engineer, Data Scientist, or AI Application Developer.
• Strong programming skills in Python (TensorFlow, PyTorch, Scikit-learn); familiarity with LangChain, Hugging Face, OpenAI API is a plus.
• Experience in model deployment, serving, and optimization (FastAPI, Flask, Django, or Node.js).
• Proficiency with databases (SQL and NoSQL: MySQL, PostgreSQL, MongoDB).
• Hands-on experience with cloud ML services (SageMaker, Vertex AI, Azure ML) and DevOps tools (Docker, Kubernetes, CI/CD).
• Knowledge of MLOps practices: model versioning, monitoring, retraining, experiment tracking.
• Familiarity with frontend frameworks (React.js, Angular, Vue.js) for building AI-driven interfaces (nice to have).
• Strong understanding of data structures, algorithms, APIs, and distributed systems.
• Excellent problem-solving, analytical, and communication skills.

About HealthAsyst

HealthAsyst is a leading technology company based out of Bangalore India focusing on the US healthcare market with a product and services portfolio. 

HealthAsyst IT services division offers a whole gamut of software services, helping clients effectively address their operational challenges. The services include product engineering, maintenance, quality assurance, custom-development, implementation & healthcare integration. The product division of HealthAsyst partners with leading EHR, PMS and RIS vendors to provide cutting-edge patient engagement solutions to small and large provider group in the US market.

Role and Responsibilities

• Ability to face customer as AI expert, assisting in client consultations.
• Own the solutioning process, Align AI projects with client requirements.
• Drive the development of AI and ML solutions that address business problems.
• Collaborate with development teams and solution architects to develop and integrate AI solutions.
• Monitor and evaluate the performance and impact of AI and ML solutions and ensure continuous improvement and optimization.
• Design and develop AI/ML models to solve complex business problems using supervised, unsupervised, and reinforcement learning techniques..
• Build, train, and evaluate machine learning pipelines, including data preprocessing, feature engineering, and model tuning.
• Establish and maintain best practices and standards for architecture, AI and ML models, innovation, and new technology evaluation.
• Collaborate with software developers to integrate AI capabilities into applications and workflows
• Develop APIs and microservices to serve AI models for real-time or batch inference.
• Foster a culture of innovation and collaboration within the COE, across teams and provide mentorship/guidance to the team members.
• Implement responsible AI practices, including model explainability, fairness, bias detection, and compliance with ethical standards.
• Experience in deploying AI models into production environments using tools like TensorFlow Serving, TorchServe, or container-based deployment (Docker, Kubernetes)

Qualifications

• 3+ years of experience in AI and ML projects.
• Proven track record of delivering successful AI and ML solutions that address complex business problems.
• Expertise in design, development, deployment and monitoring of AI ML solutions in production.
• Proficiency in various AI and ML techniques and tools, such as deep learning, NLP, computer vision, ML frameworks, cloud platforms, etc.
• 1+ year experience in building Generative AI applications leveraging Prompt Engineering and RAG
• Preference to candidates with experience in Agentic AI, MCP and A2A (Agent2Agent) protocol.
• Strong leadership, communication, presentation and stakeholder management skills.
• Ability to think strategically, creatively and analytically, and to translate business requirements into AI and ML solutions.
• Passion for learning and staying updated with the latest developments and trends in the field of AI and ML.
• Demonstrated commitment to ethical and socially responsible AI practices

Employee Benefits: 

HealthAsyst provides the following health, and wellness benefits to cover a range of physical and mental well-being for its employees.

• Bi-Annual Salary Reviews 
• Flexible working hours
• 3 days Hybrid model
• GMC (Group Mediclaim): Provides Insurance coverage of Rs. 3 lakhs + a corporate buffer of 2 Lakhs per family. This is a family floater policy, and the company covers all the employees, spouse, and up to two children 
• Employee Wellness Program- HealthAsyst offers unlimited online doctor consultations for self and family from a range of 31 specialties for no cost to employees. And OPD consultations with GP Doctors are available in person for No Cost to employees 
• GPA (Group Personal Accident): Provides insurance coverage of Rs. 20 lakhs to the employee against the risk of death/injury during the policy period sustained due to an accident 
• GTL (Group Term Life): Provides life term insurance protection to employees in case of death. The coverage is one time of the employee’s CTC 
• Employee Assistance Program: HealthAsyst offers complete confidential counselling services to employees & family members for mental wellbeing 
• Sponsored upskills program: The company will sponsor up to 1 Lakh for certifications/higher education/skill upskilling.
• Flexible Benefits Plan – covering a range of components like 

a.     National Pension System. 

b.    Internet/Mobile Reimbursements. 

c.     Fuel Reimbursements. 

d.    Professional Education Reimbursements. 

We're Hiring: Machine Learning & Data Science Engineer

Location: Gurugram / Bengaluru (Full-time, In-Office)

Salary: Up to ₹2.5 Cr

Preferred Qualifications: PhDs, Tier-1 Grads (IITs, IISc, top global universities)

Join a stealth, VC-backed startup operating across the US, India, and EU, shaping the future of AI-driven Observability utilizing LLMs, Generative AI, and cutting-edge ML technologies. Collaborate with visionary founders experienced in scaling billion-dollar products.

🔍 What You’ll Do:

- Develop advanced time series models for anomaly detection & forecasting

- Create LLM-powered Root Cause Analysis systems employing causal inference & ML techniques

- Innovate using LLMs for enhanced time series comprehension

- Build real-time ML pipelines & scalable MLOps workflows

- Utilize Bayesian methods, causality, counterfactuals, and agent evaluation frameworks

- Handle extensive datasets in Python (TensorFlow, PyTorch, Scikit-Learn, Statsmodels, etc.)

✅ What We’re Looking For:

- Minimum 5 years of experience in ML, time series, and causal analytics

- Proficiency in Python & the ML ecosystem

- In-depth understanding of causal inference, Bayesian statistics, LLMs

- Background in ML Ops, scalable systems, and production deployment

- Additional expertise in Observability, AI agents, or LLM Ops is a plus

💡 Why Join:

- Contribute to building a groundbreaking product from inception

- Tackle real-world impactful challenges alongside a top-tier team

- Engage in a culture that prioritizes ownership, agility, and creativity

Apply here: https://whitetable.ai/form/machine-learning-data-science-engineer-dc784b

🌍 We’re Hiring: Senior Field AI Engineer | Remote | Full-time

Are you passionate about pioneering enterprise AI solutions and shaping the future of agentic AI?

Do you thrive in strategic technical leadership roles where you bridge advanced AI engineering with enterprise business impact?

We’re looking for a Senior Field AI Engineer to serve as the technical architect and trusted advisor for enterprise AI initiatives. You’ll translate ambitious business visions into production-ready applied AI systems, implementing agentic AI solutions for large enterprises.

What You’ll Do:

🔹 Design and deliver custom agentic AI solutions for mid-to-large enterprises

🔹 Build and integrate intelligent agent systems using frameworks like LangChain, LangGraph, CrewAI

🔹 Develop advanced RAG pipelines and production-grade LLM solutions

🔹 Serve as the primary technical expert for enterprise accounts and build long-term customer relationships

🔹 Collaborate with Solutions Architects, Engineering, and Product teams to drive innovation

🔹 Represent technical capabilities at industry conferences and client reviews

What We’re Looking For:

✔️ 7+ years of experience in AI/ML engineering with production deployment expertise

✔️ Deep expertise in agentic AI frameworks and multi-agent system design

✔️ Advanced Python programming and scalable backend service development

✔️ Hands-on experience with LLM platforms (GPT, Gemini, Claude) and prompt engineering

✔️ Experience with vector databases (Pinecone, Weaviate, FAISS) and modern ML infrastructure

✔️ Cloud platform expertise (AWS, Azure, GCP) and MLOps/CI-CD knowledge

✔️ Strategic thinker able to balance technical vision with hands-on delivery in fast-paced environments

✨ Why Join Us:

• Drive enterprise AI transformation for global clients
• Work with a category-defining AI platform bridging agents and experts
• High-impact, customer-facing role with strategic influence
• Competitive benefits: medical, vision, dental insurance, 401(k)

🌍 We’re Hiring: Customer Facing Data Scientist (CFDS) | Remote | Full-time

Are you passionate about applied data science and enjoy partnering directly with enterprise customers to deliver measurable business impact?

Do you thrive in fast-paced, cross-functional environments and want to be the face of a cutting-edge AI platform?

We’re looking for a Customer Facing Data Scientist to design, develop, and deploy machine learning applications with our clients, helping them unlock the value of their data while building strong, trusted relationships.

What You’ll Do:

🔹 Collaborate directly with customers to understand their business challenges and design ML solutions

🔹 Manage end-to-end data science projects with a customer success mindset

🔹 Build long-term trusted relationships with enterprise stakeholders

🔹 Work across industries: Banking, Finance, Health, Retail, E-commerce, Oil & Gas, Marketing

🔹 Evangelize the platform, teach, enable, and support customers in building AI solutions

🔹 Collaborate internally with Data Science, Engineering, and Product teams to deliver robust solutions

What We’re Looking For:

✔️ 5–10 years of experience solving complex data problems using Machine Learning

✔️ Expert in ML modeling and Python coding

✔️ Excellent customer-facing communication and presentation skills

✔️ Experience in AI services or startup environments preferred

✔️ Domain expertise in Finance is a plus

✔️ Applied experience with Generative AI / LLM-based solutions is a plus

✨ Why Join Us:

• High-impact opportunity to shape a new business vertical
• Work with next-gen AI technology to solve real enterprise problems
• Backed by top-tier investors with experienced leadership
• Recognized as a Top 5 Data Science & ML platform by G2
• Comprehensive benefits: medical, vision, dental insurance, 401(k)

🌍 We’re Hiring: AI Success & Solutions (Lead / Manager / Director) | Remote | Full-time

Are you passionate about bridging AI technology with real business impact?

Do you enjoy working customer-facing, driving solution delivery, and ensuring measurable outcomes?

We’re looking for specialists in AI Success & Solutions to lead end-to-end delivery of enterprise AI projects. This role blends Solutions Architecture with Customer Success, partnering with clients to turn AI capabilities into tangible business value.

What You’ll Do:

🔹 Partner with Sales & Data Science to understand client challenges and define success criteria

🔹 Design solution architecture and data pipelines tailored to each use case

🔹 Own post-sale execution: manage projects, facilitate deployment, and track measurable outcomes

🔹 Ensure operational excellence with documentation, version control, and team coordination

🔹 Identify growth opportunities and act as a trusted strategic advisor to clients

What We’re Looking For:

✔️ 6+ years in hybrid technical + customer-facing roles (Solutions Architect, Customer Success, Engagement Manager)

✔️ Experience with applied Data Science, ML, GenAI (LLM prompting, RAG)

✔️ Proven ability to deliver AI or data-driven solutions in consulting or startup environments

✔️ Excellent storytelling and business value articulation for technical and executive audiences

✔️ Strong project management, ownership, and attention to detail

✔️ Global client experience preferred; professional fluency in English required

✨ Why Join Us:

• Drive measurable impact for Fortune 500 customers worldwide
• Be part of a category-defining AI company bridging agents and experts
• Own strategic accounts end-to-end and shape modern AI success
• Work with a high-performance, cross-functional team
• Globally competitive compensation & benefits