Gen AI + MLOps Developer

Gen AI + MLOps Developer

Experience

510 Years

Location

PAN India / Hybrid / Work from Office – As per project requirement

Job Summary

We are looking for an experienced Gen AI + MLOps Developer to design, develop, deploy, and maintain AI/ML and Generative AI solutions at scale. The ideal candidate should have strong hands-on experience in Python, Machine Learning, LLMs, Generative AI, MLOps, cloud platforms, CI/CD, model deployment, and production monitoring.

The candidate will work closely with data scientists, ML engineers, application developers, and business stakeholders to take AI solutions from experimentation to reliable production deployment.

Key Responsibilities

• Design and develop Generative AI and Machine Learning solutions using Python.
• Develop and integrate LLM-based applications, including prompt engineering, RAG, embeddings, vector databases, and AI agents.
• Build and maintain scalable ML/AI pipelines for model training, validation, deployment, and monitoring.
• Implement MLOps practices across the ML lifecycle, including CI/CD, model versioning, experiment tracking, model registry, and automated deployment.
• Deploy ML and Gen AI models using Docker, Kubernetes, APIs, and cloud services.
• Develop automated pipelines using tools such as MLflow, Kubeflow, Airflow, Jenkins, GitHub Actions, or Azure DevOps.
• Implement model and application monitoring, logging, performance tracking, drift detection, and alerting.
• Work with cloud platforms such as AWS, Azure, or Google Cloud for AI/ML workloads.
• Build secure and scalable inference solutions for LLM and ML models.
• Optimize models for latency, scalability, cost, and reliability.
• Collaborate with Data Scientists and AI Engineers to productionize ML and Gen AI models.
• Implement responsible AI, security, governance, and access-control practices.
• Troubleshoot production issues and continuously improve AI/ML platforms.

Required Technical Skills

Programming

• Strong hands-on experience in Python
• REST APIs, FastAPI/Flask
• SQL and data processing

Machine Learning

• Supervised and unsupervised learning
• Model training, evaluation, feature engineering
• Scikit-learn, Pandas, NumPy
• Experience with PyTorch and/or TensorFlow

Generative AI / LLM

• Strong understanding of Generative AI and Large Language Models
• LLMs such as GPT, Llama, Mistral, Gemini, Claude, etc.
• Prompt Engineering
• RAG (Retrieval-Augmented Generation)
• Embeddings and vector search
• Vector databases such as Pinecone, FAISS, Chroma, Weaviate, or Milvus
• LangChain, LlamaIndex, or similar frameworks
• Fine-tuning / LoRA / PEFT is an advantage
• Experience developing AI Agents / Agentic AI is preferred

MLOps / DevOps

• MLflow / Kubeflow
• Docker and Kubernetes
• CI/CD pipelines
• Git/GitHub/GitLab
• Jenkins / GitHub Actions / Azure DevOps
• Model versioning and model registry
• Model monitoring and observability
• Automated testing and deployment

Cloud

Hands-on experience with one or more:

• AWS
• Microsoft Azure
• Google Cloud Platform

Experience with cloud AI/ML services such as SageMaker, Azure Machine Learning, Vertex AI, or equivalent is preferred.

Preferred Skills

• Gen AI application architecture
• Agentic AI / AI Agents
• NLP and Deep Learning
• Hugging Face Transformers
• NVIDIA GPU / CUDA fundamentals
• LLMOps
• Data Engineering concepts
• Kubernetes-based AI deployments
• Model optimization and inference optimization
• AI security and governance

Education