Machine Learning Engineer

Job Title : MLOps Engineer

Mode: Hybrid

Experience : 4 to 7 Years

Location : Hyderabad (Priority)/Bengaluru locations only

Notice Period : Immediate Joiner

Job Summary:

We are looking for a skilled and proactive ML Engineer with strong expertise in Python, Databricks, and Machine Learning model development. The ideal candidate should be proficient in building scalable data pipelines and deploying ML models, with a working knowledge of MLOps principles and tooling. This role offers an opportunity to work on impactful AI/ML initiatives in a collaborative environment.

Key Responsibilities:

• Develop and maintain machine learning pipelines for training, testing, and deploying models

• Design and implement infrastructure for managing and monitoring machine learning models

• Work with data scientists to build scalable, efficient, and automated model training and testing processes

• Collaborate with software engineers to integrate machine learning models into production systems

• Automate and optimize the deployment and scaling of machine learning models in a distributed computing environment

• Monitor and troubleshoot machine learning systems and infrastructure to ensure high availability and performance

• Develop and maintain documentation and best practices for MLOps processes and procedures.

Experience:

Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field

• 3+ years of experience in MLOps or related field, including building and deploying machine learning models at scale

•Proficiency in programming languages such as Python, Java, and C++

•Experience with machine learning frameworks such as TensorFlow, PyTorch, and Keras

• Experience with containerization technologies such as Docker and Kubernetes

• Strong understanding of DevOps principles and practices

• Experience with cloud computing platforms such as AWS, Azure, or Google Cloud

Key Responsibilities

• Design, build, and deploy machine learning and AI models that power Transient.AI's core products (research

automation, document intelligence, investor matching, and workflow orchestration).

• Work on applied NLP/LLM systems, including retrieval-augmented generation, structured extraction from

unstructured financial documents, and model evaluation pipelines.

• Partner closely with product and founding engineers to translate capital markets workflows into scalable AI

systems.

• Own model performance, reliability, and cost — from experimentation through production deployment.

• Build and maintain data pipelines, feature stores, and evaluation frameworks to support rapid iteration.

• Ensure systems meet the compliance, auditability, and security standards required in regulated financial

environments.

What We're Looking For

• 5+ years of experience building and deploying machine learning or AI systems in production.• Strong hands-on experience with Python and modern ML/AI frameworks (PyTorch, TensorFlow, Hugging Face,

LangChain, or equivalent).

• Experience with LLMs — fine-tuning, prompt engineering, RAG architectures, or agentic systems — is highly

valued.

• Solid grounding in data structures, distributed systems, and MLOps practices (model serving, monitoring,

versioning).

• Prior experience at a strong product company, high-growth startup, or a top-tier engineering background

• Comfort operating in an early-stage, high-ownership environment with limited process and high ambiguity.

• Exposure to fintech, capital markets, or other regulated industries is a plus, though not mandatory

Job Description:

We are seeking a highly skilled Machine Learning Engineer to join our team. The ideal candidate will have a strong background in Natural Language Processing (NLP), Large Language Models (LLMs), and Python programming.

You will work closely with data scientists, product managers, and data engineers to design, develop, and deploy high-performance AI/ML models and integrate generative AI solutions into existing workflows.

Your responsibilities will include:

• Collaborating with cross-functional teams to design and deliver high-performance AI models, including NLP, computer vision, semantics engines, linguistic analysis, risk management, and time-series prediction models. Integrating generative AI solutions into existing workflow systems.
• Developing and maintaining the ML Operations CI/CD pipeline for seamless deployment and monitoring. Training, tuning, and optimizing AI models and algorithms for enhanced performance.
• Implementing complex real-time data and AI/ML applications to capture knowledge and automate decision-making processes.
• Creating ML/AI models for business teams and establishing metrics to track their accuracy and performance. Overseeing the full lifecycle of algorithm development, from ideation to deployment and monitoring. Evaluating and ranking ML algorithms based on their potential success in solving specific problems.
• Serving as an internal resource for AI/ML needs, providing guidance and insights to stakeholders during strategic discussions.

Required Experience and Skills:

Machine Learning:

• Proficient in generative AI techniques, prompt engineering, and Retrieval-Augmented Generation (RAG) (3+ years).
• Experience with Large Language Models (LLMs) such as OpenAI, Gemini, LLAMA, and other state-of-the-art models (3+ years).
• Expertise in using ML/AI libraries such as Pandas, NumPy, PyTorch, TensorFlow, Keras, BERT, LayoutLM, and traditional ML algorithms (5+ years).
• Experience with distributed ML/AI training libraries/models: Koalas, Horovod, DDP.

Python Programming and Software Engineering:

• Expertise in Pythonic clean coding practices, including the use of decorators, generators, and descriptors (5+ years).
• Strong understanding of software design principles such as DRY, OAOO, YAGNI, KIS, EAFP/LBYL, and defensive programming (2+ years).
• Proficient in software design concepts focusing on cohesion and coupling (2+ years). Knowledge of SOLID principles (2+ years).

Education and Experience:

• Minimum Bachelor's degree or foreign equivalent in Computer Science, Electrical Engineering, or a closely related field.
• At least 5 years of experience as a software engineer and 5 years of ML-related programming.

ML DEVELOPER

Hyperworks Imaging is a cutting-edge technology company based out of Bengaluru, India since 2016. Our team uses the latest advances in deep learning and multi-modal machine learning techniques to solve diverse real world problems. We are rapidly growing, working with multiple companies around the world.

JOB OVERVIEW

We are seeking a talented and results-oriented ML Developer to join our growing team in India. In this role, you will be responsible for developing and implementing new advanced ML algorithms and AI agents for creating AI assistants of the future. 

The ideal candidate will work on a complete ML pipeline starting from extraction, transformation and analysis of data to developing novel ML algorithms. The candidate will implement latest research papers and closely work with various stakeholders to ensure data-driven decisions and integrate the solutions into a robust ML pipeline.

RESPONSIBILITIES:

• Create AI agents using Model Context Protocols (MCPs), Claude Code, DsPy etc.
• Develop custom evals for AI agents.
• Build and maintain ML pipelines
• Optimize and evaluate ML models to ensure accuracy and performance.
• Define system requirements and integrate ML algorithms into cloud based workflows.
• Write clean, well-documented, and maintainable code following best practices

REQUIREMENTS:

• 2-3+ years of experience in data science, machine learning, or a similar role.
• Demonstrated expertise with python, PyTorch, and TensorFlow.
• Graduated/Graduating with B.Tech/M.Tech/PhD degrees in Electrical Engg./Electronics Engg./Computer Science/Maths and Computing/Physics
• Has done coursework in Linear Algebra, Probability, Image Processing, Deep Learning and Machine Learning.
• Has demonstrated experience with Model Context Protocols (MCPs), DSPy, AI Agents, MLOps etc

WHO CAN APPLY:

Only those candidates will be considered who,

• have relevant skills and interests
• can commit full time
• Can show prior work and deployed projects
• can start immediately

Please note that we will reach out to ONLY those applicants who satisfy the criteria listed above.

SALARY DETAILS: Commensurate with experience.

JOINING DATE: Immediate

JOB TYPE: Full-time

Sr Engineer – Artificial Intelligence

Job Summary 

As an AI Engineer at Emerson, you will be responsible for analysing complex data sets to

identify trends, develop predictive models, and provide actionable insights. You will work closely

with cross-functional teams to understand business needs and deliver data-driven solutions that

enhance decision-making and drive business growth.

 In This Role, Your Responsibilities Will Be:

 Analyze large, complex data sets using statistical methods and machine learning

techniques to extract meaningful insights.

 Develop and implement predictive models and algorithms to solve business problems

and improve processes.

 Create visualizations and dashboards to effectively communicate findings and insights to

stakeholders.

 Work with data engineers, product managers, and other team members to understand

business requirements and deliver solutions.

 Clean and preprocess data to ensure accuracy and completeness for analysis.

 Prepare and present reports on data analysis, model performance, and key metrics to

stakeholders and management.

 Participate in regular Scrum events such as Sprint Planning, Sprint Review, and Sprint

Retrospective

 Stay updated with the latest industry trends and advancements in data science and

machine learning techniques.

For This Role, You Will Need:

 Bachelor’s degree in computer science, Data Science, Statistics, or a related field or a

master's degree or higher is preferred.

 Total 5-7 years of industry experience

 More than 3 years of experience in a data science or analytics role, with a strong track

record of building and deploying models.

 Proficiency in programming languages such as Python or R, and experience with data

manipulation libraries (e.g., pandas, NumPy).

 Excellent understanding of Agentic Frameworks like Microsoft Agent Framework.

 Experience with NLP, NLG, and Large Language Models Open Source as well as Cloud

based models.

 Experience with SQL and NoSQL databases such as MongoDB, Cassandra, Vector

databases

 Experience with Dockers, Asynchronous Data Orchestrators, environments etc.

 Strong analytical and problem-solving skills, with the ability to work with complex data

sets and extract actionable insights.

 Excellent verbal and written communication skills, with the ability to present complex

technical information to non-technical stakeholders.

Preferred Qualifications that Set You Apart:

 Prior experience in engineering domain would be nice to have

 Prior experience in working with teams in Scaled Agile Framework (SAFe) is nice to

have

 Possession of relevant certification/s in data science from reputed universities

specializing in AI.

 Familiarity with cloud platforms, Microsoft Azure is preferred

 Ability to work in a fast-paced environment and manage multiple projects simultaneously.

 Strong analytical and troubleshooting skills, with the ability to resolve issues related to

model performance and infrastructure.

Description

We’re seeking a highly skilled, execution-focused Senior Data Scientist with a minimum of 5 years of experience. This role demands hands-on expertise in building, deploying, and optimizing machine learning models at scale, while working with big data technologies and modern cloud platforms. You will be responsible for driving data-driven solutions from experimentation to production, leveraging advanced tools and frameworks across Python, SQL, Spark, and AWS. The role requires strong technical depth, problem-solving ability, and ownership in delivering business impact through data science.

Responsibilities

• Design, build, and deploy scalable machine learning models into production systems.
• Develop advanced analytics and predictive models using Python, SQL, and popular ML/DL frameworks (Pandas, Scikit-learn, TensorFlow, PyTorch).
• Leverage Databricks, Apache Spark, and Hadoop for large-scale data processing and model training.
• Implement workflows and pipelines using Airflow and AWS EMR for automation and orchestration.
• Collaborate with engineering teams to integrate models into cloud-based applications on AWS.
• Optimize query performance, storage usage, and data pipelines for efficiency.
• Conduct end-to-end experiments, including data preprocessing, feature engineering, model training, validation, and deployment.
• Drive initiatives independently with high ownership and accountability.
• Stay up to date with industry best practices in machine learning, big data, and cloud-native deployments.

Requirements

• Minimum 5 years of experience in Data Science or Applied Machine Learning.
• Strong proficiency in Python, SQL, and ML libraries (Pandas, Scikit-learn, TensorFlow, PyTorch).
• Proven expertise in deploying ML models into production systems.
• Experience with big data platforms (Hadoop, Spark) and distributed data processing.
• Hands-on experience with Databricks, Airflow, and AWS EMR.
• Strong knowledge of AWS cloud services (S3, Lambda, SageMaker, EC2, etc.).
• Solid understanding of query optimization, storage systems, and data pipelines.
• Excellent problem-solving skills, with the ability to design scalable solutions.
• Strong communication and collaboration skills to work in cross-functional teams.

Benefits

• Best-in-class salary: We hire strong talent and compensate accordingly.
• Proximity Talks: Meet and learn from designers, engineers, product leaders, and AI practitioners.
• Continuous learning: Work with a world-class team and stay close to the latest in AI, engineering, and product development.
• High-impact work: Build AI-first systems and products used at scale by global clients.

About Us

Proximity is the trusted technology, design, and consulting partner for some of the biggest Sports, Media, and Entertainment companies in the world. We’re headquartered in San Francisco and have offices in Palo Alto, Dubai, Mumbai, and Bangalore.

Since 2019, Proximity has built high-impact, scalable products used by millions of users every day. Today, we are a global team of engineers, designers, product managers, and experts solving complex problems and building cutting-edge technology at scale.

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day.

Our India Global Capability Center isn't just supporting global operations—we’re leading global innovation. After scaling rapidly into a best-in-class hub, we deliver the product innovation and enterprise capabilities that accelerate our global growth, profitability, and scale. As we expand Smartsheet India, we’re searching for Senior AI/ML Ops Engineers who crave variety and ownership. You’ll have the opportunity to work across multiple teams and disciplines, building a versatile skillset while solving the complex challenges of a global platform.

You Will:

• Designing, Developing and overseeing the strategy and architecture of scalable and reliable AI/ML Ops platforms / pipelines
• Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable
• CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools
• Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms
• Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable
• Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time.
• Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable
• Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users
• Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production.
• Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow.
• Security & Compliance: Implementing data security measures, ensuring compliance with data governance policies, and protecting sensitive data
• Technology Evaluation and Innovation: Staying abreast of emerging data technologies and exploring opportunities for innovation to improve the organisation’s data infrastructure
• Troubleshooting and Problem Solving: Diagnosing and resolving complex data-related issues, ensuring the stability and reliability of the data platform
• Perform other duties as assigned

You Have:

• Enterprise SaaS software solutions with high availability and scalability
• Solution handling large scale structured and unstructured data from varied data sources
• Experience in building and maintaining AI/ML Ops platform systems ensuring scalability, reliability, efficiency and security
• Working with Product engineering team to influence designs with data, AI and analytics use cases in mind
• In depth experience in System design, AI/ML Frameworks and tools involving large Petabytes of data with Databricks Lakehouse ecosystem
• AI/MLOps workflows on Databricks , MLFlow, Mosaic AI Agent Framework, Unity Catalog, Vector Search, Knowledge Graph
• Knowledge of AI/ML frameworks like LangChain, LangGraph for AI/ML Ops pipeline integration
• Cloud Platforms: Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP). Experience in AWS hosted data platform is preferable
• Programming languages like Python and SQL
• Modern software engineering practices like Kubernetes, CI/CD, IAC tools (Preferably Terraform), Observability, monitoring and alerting
• Solution Cost Optimisations and design to cost
• Legally eligible to work in India on an ongoing basis

Get to Know Us:

At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.

Equal Opportunity Employer:

Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, India, and Singapore. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information. 

If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.

Job application link : https://grnh.se/z7qx2ehx1us

AI/ML Engineer AI Operating System for Capital Markets Location Bangalore/Chennai Experience 5+ years Function Artificial Intelligence / Machine Learning Employment Type About Transient.AI Full-time Transient.AI is building a next-generation AI Operating System for capital markets — a unified intelligence layer that connects research, trading, compliance, and sales functions at banks and hedge funds. Today, these teams largely operate on disconnected legacy systems, forcing manual, expensive workarounds. Transient.AI replaces that fragmentation with a single AI-native layer built for institutional-grade compliance, security, and auditability. The company already has live products in market, including Caddie.AI (a research automation tool that cuts hedge fund research time significantly), ClarityRIA (helping sales teams identify the right investors in seconds), and CapFlo.AI (automated parsing of complex derivatives contracts). Founded by former traders and technologists from Goldman Sachs, Credit Suisse, UBS, and McKinsey, Transient.AI is headquartered in New York, with teams in Miami, Singapore, and India. The company has raised Series A funding and is scaling its engineering and product organization globally. Role Overview Transient.AI is hiring an experienced AI/ML Engineer to join its India engineering team in Bangalore/Chennai. This is a hands-on, build-from-scratch role — you'll be designing and shipping the core machine learning systems that power the company's flagship products, working closely with founders and senior engineers rather than inheriting existing infrastructure. Key Responsibilities • Design, build, and deploy machine learning and AI models that power Transient.AI's core products (research automation, document intelligence, investor matching, and workflow orchestration). • Workonapplied NLP/LLMsystems, including retrieval-augmented generation, structured extraction from unstructured financial documents, and model evaluation pipelines. • Partner closely with product and founding engineers to translate capital markets workflows into scalable AI systems. • Ownmodelperformance, reliability, and cost — from experimentation through production deployment. • Build and maintain data pipelines, feature stores, and evaluation frameworks to support rapid iteration. • Ensuresystems meet the compliance, auditability, and security standards required in regulated financial environments. What We're Looking For • 5+years ofexperience building and deploying machine learning or AI systems in production.• Strong hands-on experience with Python and modern ML/AI frameworks (PyTorch, TensorFlow, Hugging Face, LangChain, or equivalent). • Experience with LLMs — fine-tuning, prompt engineering, RAG architectures, or agentic systems — is highly valued. • Solid grounding in data structures, distributed systems, and MLOps practices (model serving, monitoring, versioning). • Prior experience at a strong product company, high-growth startup, or a top-tier engineering background • Comfort operating in an early-stage, high-ownership environment with limited process and high ambiguity. • Exposure to fintech, capital markets, or other regulated industries is a plus, though not mandatory. WhyJoin Transient.AI • Build core AI systems from the ground up — not maintain legacy code. • Workdirectly with founders who have deep, first-hand Wall Street experience (Goldman Sachs, Credit Suisse, UBS, McKinsey). • JoinaSeries A-funded company solving a real, expensive problem for institutional finance. • Bepart ofasmall, global team with outsized ownership and impact. .

About Us:

The QX Impact was launched with a mission to make A.I accessible and affordable and deliver AI Products/Solutions at scale for the enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights; businesses will continue to face challenges to better understand their customers and even lose them. Secondly, without insights businesses won't’ be able to deliver differentiated products/services; and finally, without insights, businesses can’t achieve a new level of “Operational Excellence” is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.

Role Overview

We are seeking a Machine Learning Engineer to lead the end-to-end development of production-grade analytical applications. This is a high-impact role requiring a blend of deep statistical modeling and machine learning. You will be responsible transforming raw consolidated data into high-accuracy forecasts through advanced feature engineering, rigorous model selection, and statistical validation.

This role is for an engineer who thrives in the research-to-code transition, ensuring that every model is mathematically sound, resistant to overfitting, and optimized for high-dimensional manufacturing data.

Responsibilities:

• Feature Engineering & Discovery: Design and build complex feature sets for diverse problem types, including behavioural features for churn, sensor-based lags for maintenance, and seasonal encodings for demand forecasting.
• Model Selection & Optimization: Conduct systematic experimentation across diverse algorithms (e.g., XGBoost, LightGBM, Prophet, or Deep Learning) to identify the best-performing models.
• Model Training & Testing: Develop, train, tune, and test a variety of ML architectures including time-series, classification and regression.
• Statistical Validation & Evaluation: Define and track complex evaluation metrics tailored to manufacturing, such as MAPE, RMSE, etc., while performing deep-dive bias-variance analysis.
• EDA & Research: Perform exploratory data analysis on consolidated "Gold" layer data to uncover hidden drivers of business outcomes and identify correlations between external signals.
• Refinement & Performance Tuning: Address critical modeling challenges including bias-variance tradeoffs, class imbalance, and overfitting to ensure models generalize to real-world production data.

Skills & Requirements:

• 3+ Years of Experience: Proven track record of developing and delivering production-grade ML models across multiple domains (Sales, Finance, Manufacturing, or Supply Chain).
• Mastery of the Python Ecosystem: Expert-level skills in Pandas, NumPy, Scikit-learn, and SciPy.
• Advanced Algorithmic Knowledge: Deep expertise in supervised and unsupervised learning, specifically ensemble methods (Boosting/Bagging) and time-series frameworks.
• Statistical Foundations: Strong grasp of hypothesis testing, probability distributions, and the mathematical principles behind model evaluation and optimization.
• SQL Proficiency: Expert ability to manipulate data within consolidated database layers to create the "Silver" feature sets required for training.
• Education: Bachelor’s or Master’s degree in a quantitative field (e.g., Data Science, Statistics, Mathematics, or Computer Science).
• Cloud Awareness: Experience with Azure Machine Learning or similar cloud modelling environments.
• Engineering Familiarity: Basic understanding of Docker, MLflow, or FastAPI for handing models off to deployment teams.

Personal Attributes:

• Strong problem-solving skills with a passion for data architecture.
• Excellent communication skills with the ability to explain complex data concepts to non-technical stakeholders.
• Highly collaborative, capable of working with cross-functional teams.
• Ability to thrive in a fast-paced, agile environment while managing multiple priorities effectively.

Competencies:

• Tech Savvy - Anticipating and adopting innovations in business-building digital and technology applications.
• Self-Development - Actively seeking new ways to grow and be challenged using both formal and informal development channels.
• Action Oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
• Customer Focus - Building strong customer relationships and delivering customer-centric solutions.
• Optimize Work Processes - Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.

Why Join Us?

• Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
• Work on impactful projects that make a difference across industries.
• Opportunities for professional growth and continuous learning.
• Competitive salary and benefits package.

Application Details

Ready to make an impact? Apply today and become part of the QX Impact team!

Job Title : Data Engineer – Databricks

Experience : 6+ Years

Location : Noida / Hyderabad / Chennai / Pune / Bengaluru (Hybrid)

Shift : IST (Normal Shift)

Job Summary :

We are seeking an experienced Data Engineer with strong expertise in Databricks, Snowflake, Python, and Spark to build and optimize scalable data pipelines and support AI/ML model deployments. The ideal candidate should have experience working with cloud-based data platforms and preferably possess exposure to the Healthcare domain.

Required Skills :

• Databricks (Preferred)
• Snowflake
• Python
• Apache Spark
• SQL
• Azure Cloud
• Kubernetes
• Apache Airflow
• GitHub & CI/CD Pipelines
• AI/ML Model Deployment
• Data Analytics

Preferred :

• Experience in the Healthcare domain.
• Strong understanding of scalable data engineering architectures and best practices.