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Senior AI Engineer at Digital Convergence Technologies Ā· Pune Ā· 6 - 8 years Ā· ₹45L - ₹50L / yr Ā· Profitable Ā· Posted 12 Dec 2025

Digital Convergence Technologies's logo

Senior AI Engineer

sanjana L's profile picture
Posted by sanjana L
6 - 8 yrs
₹45L - ₹50L / yr
Pune
Skills
skill iconPython
databricks
skill iconMachine Learning (ML)
Artificial Intelligence (AI)
CI/CD

We are looking for a Senior AI / ML Engineer to join our fast-growing team and help build AI-driven data platforms and intelligent solutions. If you are passionate about AI, data engineering, and building real-world GenAI systems, this role is for you!



šŸ”§ Key Responsibilities

• Develop and deploy AI/ML models for real-world applications

• Build scalable pipelines for data processing, training, and evaluation

• Work on LLMs, RAG, embeddings, and agent workflows

• Collaborate with data engineers, product teams, and software developers

• Write clean, efficient Python code and ensure high-quality engineering practices

• Handle model monitoring, performance tuning, and documentation



Required Skills

• 2–5 years of experience in AI/ML engineering

• Strong knowledge of Python, TensorFlow/PyTorch

• Experience with LLMs, GenAI, RAG, or NLP

• Knowledge of Databricks, MLOps or cloud platforms (AWS/Azure/GCP)

• Good understanding of APIs, distributed systems, and data pipelines



šŸŽÆ Good to Have

• Experience in healthcare, SaaS, or big data

• Exposure to Databricks Mosaic AI

• Experience building AI agents

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About Digital Convergence Technologies

Founded :
2018
Type :
Product
Size :
100-500
Stage :
Profitable

About

DCT is a client-focused organization that specializes in digital transformation, enterprise grade applications and cloud & software based technologies.
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• Design, develop, and deploy Machine Learning and Deep Learning models for classification, regression, recommendation systems, NLP, Computer Vision, and Generative AI applications.

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Why Join Kody Technolab Limited?

Opportunity to work on innovative AI products, Generative AI solutions, robotics integrations,

and enterprise-scale applications while collaborating with a highly skilled technology team.


Visit the Website to know more about us.

Company Website - Kody Technolab | Deep Tech Company in Robotics & AI Solution

Kody Robots | Robotics Company in India for Autonomous Robots

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Company: Timble Technologies Pvt. Ltd

Location: Gurugram (Hybrid)

Experience: 2 TO 5 Years


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Timble Glance is a high-growth AI RegTech and B2B SaaS company catering to top-tier BFSI and enterprise clients. We build cutting-edge systems powering 30+ high-scale APIs for digital identity verification, fraud detection, document intelligence, and compliance automation.

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Key Responsibilities


Ā·Ā Ā Ā Ā Ā Ā Ā Model Architecture & Deployment: Design, train, and deploy production-scale ML/Deep Learning and GenAI systems (computer vision, document intelligence, OCR, NLP, fraud risk classification, and LLM applications).

Ā·Ā Ā Ā Ā Ā Ā Ā GenAI & LLM Solutions: Develop robust LLM workflows including prompt engineering, fine-tuning, RAG pipelines, semantic search, vector indexing (Pinecone/Milvus/Chroma), and safety guardrails.

Ā·Ā Ā Ā Ā Ā Ā Ā Pipelines & Engineering: Build performant feature extraction and data pipelines; write modular, vectorized, production-grade Python (NumPy, Pandas) and advanced SQL.

Ā·Ā Ā Ā Ā Ā Ā Ā MLOps & Monitoring: Establish end-to-end MLOps/LLMOps standards—model registries, CI/CD, experiment tracking, drift detection, A/B testing, latency optimization, and cost governance.

Ā·Ā Ā Ā Ā Ā Ā Ā Responsible AI & Security: Ensure model decisions comply with enterprise data security, privacy standards, and auditability required by the BFSI sector.

Ā·Ā Ā Ā Ā Ā Ā Ā Collaboration & Ownership: Translate complex business requirements into technical roadmaps, conduct rigorous code reviews, and mentor junior engineers.


Required Qualifications & Skills


Ā·Ā Ā Ā Ā Ā Ā Ā Education: B.Tech / M.Tech in Computer Science, AI/ML, Mathematics, or a related field—Tier-1 institutes (IIT, IIIT, NIT) strongly preferred.

Ā·Ā Ā Ā Ā Ā Ā Ā Experience: 2+ years of hands-on experience developing, deploying, and maintaining ML/Deep Learning or GenAI models in production environments.

Ā·Ā Ā Ā Ā Ā Ā Ā GenAI & NLP Stack: Hands-on experience with LLMs, embeddings, RAG architectures, and frameworks such as LangChain, LlamaIndex, or Hugging Face.

Ā·Ā Ā Ā Ā Ā Ā Ā Deep Learning Frameworks: Strong proficiency in PyTorch or TensorFlow, with deep knowledge of transformer architectures and modern NLP/CV models.

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Ā·Ā Ā Ā Ā Ā Ā Ā Experience optimizing models for low latency and inference cost (e.g., ONNX, TensorRT, model quantization).

Ā·Ā Ā Ā Ā Ā Ā Ā Familiarity with workflow orchestrators such as Airflow, Prefect, or Kubeflow.

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  • We are looking for experienced AI/ML Architects to join our AI Engineering service line. In this role, you will anchor the technical delivery of enterprise AI/Agentic AI projects post deal-closure. You will take over from solution architects and lead the design, build, deployment, and optimization of AI/ML systems — ensuring production-grade quality, scalability, and compliance.Ā 
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Key Responsibilities

Architecture & Technical Leadership

Hands-on Engineering & Problem Solving

Required Qualifications

Education : B.Tech/M.Tech or equivalent in Computer Science, Data Science, or a related field.


Experience

ā— 10+ years in software architecture or engineering with 5+ years in applied AI/ML

system delivery.

ā— Experience in productionizing AI/ML models and building full-stack AI applications in

enterprise settings.

ā— Strong Python development skills; proficiency in ML/AI frameworks (PyTorch,

TensorFlow, Scikit-learn).

ā— Strong understanding of LLMs, RAG pipelines, vector databases (Weaviate, Qdrant,

Pinecone).


ā— Experience with MLOps/LLMOps tools: MLflow, Argo, KServe, Feast, Kubeflow.

ā— Proficiency in data pipeline engineering using Spark, Airflow, or DataFlow.

ā— Exposure to agent orchestration frameworks: LangChain, LangGraph, AutoGen,

CrewAI is a big plus.

ā— Cloud & Infrastructure

ā— Hands-on experience with GCP (Vertex AI, BigQuery, Document AI, AI Gateway)

and/or Azure (Azure ML, OpenAI, Synapse).

ā— Expertise in containerization (Docker) and orchestration (Kubernetes).

ā— Familiarity with Infrastructure as Code (Terraform, Pulumi, CDK).


Soft Skills

Strong architectural thinking and problem-solving in fast-paced delivery environments.

Excellent communication and collaboration skills to work across cross-functional teams and

clients.

Proactive, structured, and detail-oriented with a bias for execution.

Nice to Have

Experience in real-world deployments of Agentic AI systems or collaborative multi-agent setups.

Exposure to regulatory/ethical concerns in AI such as fairness, transparency, or bias mitigation.

Familiarity with AI observability, explainability, and governance tooling (e.g., Arize, Fiddler,

TruEra).

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Kalyani Wadnere
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Pune
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About NonStop io Technologies

NonStop io Technologies is a value-driven company with a strong focus on process-oriented software engineering. We specialize in Product Development and have a decade's worth of experience in building web and mobile applications across various domains. NonStop io Technologies follows core principles that guide its operations and believes in staying invested in a product's vision for the long term. We are a small but proud group of individuals who believe in the 'givers gain' philosophy and strive to provide value in order to seek value. We are committed to and specialize in building cutting-edge technology products and serving as trusted technology partners for startups and enterprises. We pride ourselves on fostering innovation, learning, and community engagement. Join us to work on impactful projects in a collaborative and vibrant environment.


Brief Description:

We're seeking an AI/ML Engineer to join our team. As 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 engineering teams, including software engineers, domain experts, and product managers, to deploy and integrate Applied AI/ML solutions into the products that are being built at NonStop io. Your role will involve researching cutting-edge algorithms and data processing techniques, and implementing scalable solutions to drive innovation and improve the overall user experience.


Responsibilities

ā— Applied AI/ML engineering; Building engineering solutions on top of the AI/ML tooling available in the industry today. Eg: Engineering APIs around OpenAI

ā— 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.

ā— 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

ā— 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

ā— Data Visualization: Create clear and insightful data visualizations to aid in understanding data patterns, model behaviour, and performance metrics

ā— 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

ā— Data Security and Privacy: Ensure compliance with data privacy regulations and implement security measures to protect sensitive information used in AI/ML processes

ā— 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

ā— Documentation: Maintain detailed documentation of the AI/ML development process, including code, models, algorithms, and methodologies for easy understanding and future reference.


Qualifications & Skills

ā— 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

ā— Proven experience as an AI/ML Engineer, Data Scientist, or related role, ideally with a strong portfolio of AI/ML projects

ā— Proficiency in programming languages commonly used for AI/ML. Preferably Python

ā— Familiarity with popular AI/ML libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, etc.

ā— Familiarity with popular AI/ML Models such as GPT3, GPT4, Llama2, BERT etc.

ā— Strong understanding of machine learning algorithms, statistics, and data structures

ā— Experience with data preprocessing, data wrangling, and feature engineering

ā— Knowledge of deep learning architectures, neural networks, and transfer learning

ā— Familiarity with cloud platforms and services (e.g., AWS, Azure, Google Cloud) for scalable AI/ML deployment

ā— Solid understanding of software engineering principles and best practices for writing maintainable and scalable code

ā— Excellent analytical and problem-solving skills, with the ability to think critically and propose innovative solutions

ā— Effective communication skills to collaborate with cross-functional teams and present complex technical concepts to non-technical stakeholders

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Bengaluru (Bangalore), Delhi, Gurugram, Noida, Ghaziabad, Faridabad, Chennai
4 - 15 yrs
₹30L - ₹40L / yr
skill iconMachine Learning (ML)
Natural Language Processing (NLP)
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skill iconPython
Scikit-Learn
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About the Role

Ā 

We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, MLOps, and Generative AI. The ideal candidate will have hands-on experience in building scalable ML models, deploying them in production, and working with modern AI frameworks, including GenAI technologies.

Ā 

Ā 

Ā 

Key Responsibilities

Ā 

Ā·Ā Ā Ā Ā Ā Ā Design, develop, and deploy machine learning models for real-world business problems

Ā·Ā Ā Ā Ā Ā Ā Work on end-to-end ML lifecycle: data preprocessing, model building, evaluation, deployment, and monitoring

Ā·Ā Ā Ā Ā Ā Ā Implement and manage MLOps pipelines for scalable and reproducible workflows

Ā·Ā Ā Ā Ā Ā Ā Utilize tools like MLflow for experiment tracking, model versioning, and lifecycle management

Ā·Ā Ā Ā Ā Ā Ā Develop and integrate Generative AI (GenAI) solutions such as LLM-based applications

Ā·Ā Ā Ā Ā Ā Ā Collaborate with cross-functional teams (engineering, product, business) to translate requirements into AI solutions

Ā·Ā Ā Ā Ā Ā Ā Optimize model performance and ensure production stability

Ā·Ā Ā Ā Ā Ā Ā Stay updated with the latest advancements in AI/ML and GenAI ecosystems

Ā 

Ā 

Ā 

Required Skills & Qualifications

Ā 

Ā·Ā Ā Ā Ā Ā Ā 4+ years of experience in Data Science / Machine Learning

Ā·Ā Ā Ā Ā Ā Ā Strong programming skills in Python

Ā·Ā Ā Ā Ā Ā Ā Hands-on experience with ML modeling techniques (supervised, unsupervised, NLP, etc.)

Ā·Ā Ā Ā Ā Ā Ā Solid understanding of MLOps practices and tools

Ā·Ā Ā Ā Ā Ā Ā Experience with MLflow or similar model lifecycle toolsĀ 

Ā·Ā Ā Ā Ā Ā Ā Practical experience in Generative AI (GenAI), including working with LLMs

Ā·Ā Ā Ā Ā Ā Ā Experience with libraries/frameworks like Scikit-learn, TensorFlow, PyTorch

Ā·Ā Ā Ā Ā Ā Ā Strong understanding of data structures, algorithms, and statistics

Ā·Ā Ā Ā Ā Ā Ā Experience with cloud platforms (AWS/GCP/Azure) is a plus


Good to Have

Ā 

Ā·Ā Ā Ā Ā Ā Ā Experience with LLM fine-tuning, prompt engineering, or RAG pipelines

Ā·Ā Ā Ā Ā Ā Ā Exposure to Docker, Kubernetes, and CI/CD pipelines

Ā·Ā Ā Ā Ā Ā Ā Knowledge of data engineering workflowsĀ 



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anju kushwaha
Posted by anju kushwaha
Gurugram
4 - 6 yrs
₹20L - ₹50L / yr
Generative AI (GenAI)
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Job Description:

We are seeking a versatile and highly skilled Lead AI/ML Engineer with deep expertise in Generative AI (GenAI) and Large Language Models (LLMs). This role requires a leader who can take full ownership of the

AI lifecycle—from initial architectural design to final production execution. You will lead the development of scalable AI-powered applications, demonstrating exceptional execution skills and the ability to deliver high-performance results under pressure in demanding production environments.


Machine Learning & LLM Capability:

 End-to-End ML Engineering: Build and manage comprehensive ML pipelines, including data ingestion, preprocessing, training, and evaluation using frameworks like PyTorch, TensorFlow, and Scikit-learn.  Advanced LLM Systems: Design and implement sophisticated LLM-based applications such as autonomous agents, chatbots, and complex automation tools.

 Generative AI Specialization: Architect and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases like FAISS, Pinecone, or Weaviate.

 Model Optimization: Fine-tune open-source and proprietary models (e.g., LLaMA, GPT) using advanced techniques like LoRA, QLoRA, or instruction tuning.

 Agentic Frameworks: Develop complex agentic workflows utilizing frameworks such as LangChain or LlamaIndex.

 Prompt Engineering: Implement expert-level prompt engineering, tool/function calling, and structured output generation.

 Project Ownership & Execution

 Full Lifecycle Ownership: Take complete accountability for the full ML and GenAI lifecycle, spanning data processing, model development, monitoring, and optimization.

 Architectural Leadership: Drive strategic architectural decisions for AI platforms, ensuring they are modular, scalable, and maintainable.

 Execution Excellence: Write clean, high-performance Python code following strict OOP principles and manage CI/CD pipelines for seamless project execution.

 Leadership & Mentoring: Act as a key technical leader, managing stakeholders and mentoring team members to ensure all project milestones are met with quality.

 System Integrity: Manage model and prompt versioning, experiment tracking, and comprehensive documentation for all pipelines and workflows.

 Performance Under Pressure

 Production Reliability: Ensure all AI systems maintain extreme scalability and performance under heavy production workloads, including both batch and real-time processing.

 High-Pressure Optimization: Rapidly optimize inference latency and system costs for ML and LLM systems to meet urgent business and technical requirements.

 Proactive Problem Solving: Apply strong analytical thinking to address complex challenges such as system drift, hallucinations, and latency in fast-paced environments.

 Robust Guardrails: Implement and manage strict evaluation frameworks and feedback loops to maintain system quality under stress.


Qualifications:

 Bachelor’s or Master’s degree in Computer Science, AI, ML, or a related field.

 Proven expertise in Python, system design, and scalable AI/ML architecture.

 Deep knowledge of NLP, Computer Vision, and Deep Learning models.

 Hands-on experience with Docker, Kubernetes, MLOps, and major cloud platforms (AWS, GCP, or Azure).

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Shakthi M
Posted by Shakthi M
Bengaluru (Bangalore), Mumbai
5 - 14 yrs
Best in industry
Anti money laundering
Fraud
skill iconPython
AML
skill iconDjango

Must of Skills/ExperienceĀ 

• System Design

• Python

• TensorFlow

• Google ADK or Lang Graph

• Lang Chain , Lang Graph

• Spark

• Agentic AI Design

• ML Ops

• MCP (client and server)

• FastAPI

• Doc Factory

• RAG

• Golang

• LLMs – Gemini, Open AI

• NLP

• Dev Assistant - AI based code - generation

(Qwen or Claude or Copilot)

• CI/CD

• Good in oral and written communication,

collaboration and be a team player

Good to have skillsĀ 

• DevOps with K8

• Scripting

• Java

• REST API

• UV

• ReACT

• DocFactory

• Unix

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Mayank Choudhary
Posted by Mayank Choudhary
icon

The recruiter has not been active on this job recently. You may apply but please expect a delayed response.

Pune
3 - 5 yrs
₹27L - ₹32L / yr
skill iconData Science
Artificial Intelligence (AI)
skill iconMachine Learning (ML)

Strong AI Engineer / Machine Learning Engineer profiles.

2

Mandatory (Experience 1) – Must have minimum 3+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.

3

Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.

4

Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.

5

Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.

6

Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.

7

Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.

8

Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.

9

Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.

10

Mandatory (Age) - Candidate's Age should be below 30 Years

11

Preferred (Experience 1) – Experience with MLFlow, Kubeflow, Airflow, Prefect, Feature Stores, Model Registry, or MLOps/LLMOps frameworks.

12

Preferred (Experience 2) – Experience working with Vector Databases, Spark, PySpark, distributed ML pipelines, large-scale data processing, or real-time ML systems..

13

Preferred (Experience 3) – Familiarity with Docker, Kubernetes, Azure, AWS, GCP, cloud-native AI deployments, and scalable ML architecture.

14

Preferred (Company) – Candidates from AI-first startups, Fintech, Banking, Lending, Fraud Analytics, Risk Analytics, Product Companies, SaaS organizations, or data-driven technology companies

15

Mandatory ( Pedigree) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered.

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shwetha V
Posted by shwetha V
Remote only
6 - 12 yrs
Best in industry
skill iconPython
Large Language Models (LLM)
skill iconMachine Learning (ML)
MLOps
Large Language Models (LLM) tuning
+4 more

Principal Software Engineer

Company Summary :


As the recognized global standard for project-based businesses, Deltek delivers software and information solutions to help organizations achieve their purpose. Our market leadership stems from the work of our diverse employees who are united by a passion for learning, growing and making a difference. At Deltek, we take immense pride in creating a balanced, values-driven environment, where every employee feels included and empowered to do their best work. Our employees put our core values into action daily, creating a one-of-a-kind culture that has been recognized globally. Thanks to our incredible team, Deltek has been named one of America's Best Midsize Employers by Forbes, a Best Place to Work by Glassdoor, a Top Workplace by The Washington Post and a Best Place to Work in Asia by World HRD Congress. www.deltek.com


Position Responsibilities :


About the RoleĀ 

We are seeking a highly motivated AI Solutions Engineer to join Deltek’s growing AI Center of Excellence team to design, develop, deploy, and optimize internal Artificial Intelligence and Machine Learning solutions that solve complex business challenges. The ideal candidate combines deep expertise in AI, machine learning, Generative AI, Large Language Models (LLMs), SLMs, software engineering, cloud computing, and MLOps/LLMOps to build scalable, production-grade AI applications.Ā 

The AI Solutions Engineer will collaborate with AI data scientists, architects, and engineering teams to deliver innovative AI-driven solutions while ensuring security, scalability, governance, and operational excellence. This role reports to the Senior AI Solutions Architect.Ā 

Key ResponsibilitiesĀ 

AI & Machine Learning DevelopmentĀ 

  • Design, build, train, evaluate, and deploy machine learning and deep learning models.Ā 
  • Develop Generative AI solutions using Large Language Models (LLMs) such as GPT, Claude, Gemini, Llama, and Mistral.Ā 
  • Implement Retrieval-Augmented Generation (RAG), prompt engineering, fine-tuning, and AI agent frameworks.Ā 
  • Build NLP, recommendation systems, forecasting, predictive analytics, and intelligent automation solutions.Ā 
  • Optimize model performance, scalability, latency, and cost.Ā 

Software Engineering & Solution DevelopmentĀ 

  • Develop production-grade AI applications using Python and modern software engineering practices.Ā 
  • Build APIs, microservices, and AI-powered enterprise applications.Ā 
  • Integrate AI services with enterprise systems, business applications, and data platforms.Ā 
  • Apply coding standards, automated testing, CI/CD, and version control best practices.Ā 

MLOps & AI OperationsĀ 

  • Design and implement MLOps pipelines for model development, deployment, monitoring, and lifecycle management.Ā 
  • Automate model training, validation, testing, and deployment processes.Ā 
  • Monitor model performance, data drift, hallucinations, and operational metrics.Ā 
  • Support continuous improvement and reliability of AI platforms.Ā 

Cloud & Platform EngineeringĀ 

  • Develop AI solutions on Azure, AWS, or Google Cloud platforms.Ā 
  • Leverage cloud-native AI services, containerization, Kubernetes, and serverless technologies.Ā 
  • Build scalable architectures supporting enterprise AI workloads and real-time inference.Ā 

AI Governance & SecurityĀ 

  • Ensure compliance with Responsible AI, security, privacy, and regulatory requirements.Ā 
  • Implement model governance, explainability, bias mitigation, and risk management practices.Ā 
  • Maintain standards for secure design, deployment, and operation of AI solutions.Ā 




Required QualificationsĀ 

EducationĀ 

  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related technical field.Ā 

ExperienceĀ 

  • 5+ years of software engineering or machine learning development experience.Ā 
  • 2+ years of hands-on experience developing and deploying Agentic AI, Generative AI or AI/ML solutions in production environments.Ā 

Technical SkillsĀ 

Programming & EngineeringĀ 

  • Strong expertise in Python.Ā 
  • Experience with Java, ReactJS, JavaScript, or similar programming languages.Ā 
  • Solid understanding of algorithms, data structures, APIs, and software design principles.Ā 

Artificial Intelligence & Machine LearningĀ 

  • Machine Learning and Deep Learning concepts and frameworks.Ā 
  • Model training, evaluation, optimization, and deployment.Ā 

Generative AIĀ 

  • Large Language Models (LLMs) & SLMsĀ 
  • Prompt EngineeringĀ 
  • Retrieval-Augmented Generation (RAG)Ā 
  • AI Agents and Agentic WorkflowsĀ 
  • Fine-tuning and model customizationĀ 
  • Vector embeddings and semantic searchĀ 

Frameworks & ToolsĀ 

  • PyTorch, TensorFlow, Scikit-learnĀ 
  • LangChain, LlamaIndex, Semantic Kernel, MCP, A2A and TransformersĀ 
  • FastAPI, FlaskĀ 

Data & AnalyticsĀ 

  • SQL and NoSQL databasesĀ 
  • Data pipelines, ETL, and data modelingĀ 
  • Experience with AWS, Azure and GoogleĀ 

MLOps & DevOpsĀ 

  • MLflow, Kubeflow, Azure ML, SageMakerĀ 
  • Docker and KubernetesĀ 
  • Git, GitHub, Azure DevOps, JenkinsĀ 
  • CI/CD automation and model monitoringĀ 

Cloud PlatformsĀ 

  • AWS (preferred)Ā 
  • AWS Bedrock or Azure OpenAI ServiceĀ 
  • AWS SageMakerĀ 
  • Google Vertex AIĀ 

Preferred QualificationsĀ 

  • Experience designing enterprise-scale AI platforms and products.Ā Ā 
  • Knowledge of multi-agent architectures and autonomous AI systems.Ā Ā 
  • Experience with vector databases such as Pinecone, Snowflake Cortex, Pgvector, Weaviate, Chroma, or Azure AI Search.Ā Ā 
  • Understanding of AI governance, compliance, and Responsible AI frameworks.Ā Ā 
  • Relevant certifications in Azure AI, AWS Machine Learning, or Google Cloud AI.
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Shubham Vishwakarma

Full Stack Developer - Averlon
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