AI ML Developer

Job Description

AI ML Developer

Location: Bangalore
Experience: 5+ Years

At Capgemini, we empower engineers to build intelligent, scalable AI systems that transform enterprise operations. Join our team to lead the development of cutting-edge GenAI and ML solutions that drive precision, performance, and innovation.

Your Role

As a AI ML Developer you will be responsible for designing, building, and productionizing scalable AI models and pipelines. You’ll work across the full lifecycle—from architecture to deployment—delivering high-value solutions powered by advanced LLMs and multi-agent frameworks.

In this role, you will:

• Design, build, and productionize scalable ML/GenAI models and pipelines with a focus on reliability and precision
• Develop retrieval-augmented generation (RAG) pipelines and agentic systems using advanced LLMs
• Fine-tune, optimize, and deploy transformer-based models (GPT, LLaMA, Mistral, etc.) for enterprise use cases
• Architect and implement multi-agent frameworks for tool-augmented reasoning, orchestration, and memory management
• Deliver robust APIs and services for ML/GenAI models with performance and cost optimization
• Collaborate with software engineers and DevOps teams to scale AI systems across cloud, hybrid, and on-prem environments
• Drive automation in model deployment, monitoring, retraining, and drift detection
• Ensure security, compliance, and governance in all AI solutions
• Stay ahead of GenAI, LLM, and infrastructure innovations and integrate them into the product roadmap

Your Profile

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or related field
• 5+ years of experience delivering production-grade ML/GenAI applications
• Strong proficiency in Python (3.x) and ML/DL frameworks (PyTorch, TensorFlow, Hugging Face)
• Hands-on experience with LLMs and fine-tuning methods (LoRA, PEFT, quantization)
• Deep expertise in RAG pipelines, embeddings, and vector databases (Elastic, Pinecone, Milvus)
• Applied knowledge of GenAI frameworks (LangChain, LlamaIndex, Haystack, LangGraph, AutoGen, Crew.ai)
• Strong understanding of agent-based systems (multi-agent orchestration, tool use, reasoning loops)
• Familiarity with Model Context Protocol (MCP) for secure and interoperable GenAI integrations
• Experience with cloud-native ML engineering (Azure OpenAI, AWS Bedrock) and container orchestration (Docker/Kubernetes)
• Knowledge of Responsible AI practices including transparency and ethical use
• Proficiency in MLOps practices: CI/CD for ML, monitoring, retraining, and scaling

What You’ll Love About Working Here

We offer flexible work arrangements, a collaborative culture, and continuous learning opportunities. You’ll be part of a global team driving innovation in GenAI and enterprise AI transformation.