Senior Machine Learning Engineer

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.


If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

Role : Senior Machine Learnings Engineer (AWS)

Experience : 3-6 Years

Location : Mumbai/Bangalore

Must have skills:

• Experience with LangChain, LangGraph, LlamaIndex, CrewAI, or similar Agentic AI frameworks.

• Python: Good exposure to Python (Pandas, NumPy, FastAPI, advanced Python concepts).

• AWS Bedrock: Hands-on experience with AWS Bedrock and foundation models such as Claude Haiku and Claude Sonnet.

• LLM & GenAI: Hands-on experience in developing RAG pipelines, Prompt Engineering, and LLM-based GenAI applications.

• ML Pipeline Architecture: Experience with Titan Embeddings, Amazon OpenSearch Vector Search, and vector-based retrieval.

• Agentic AI: Hands-on experience with Agentic AI frameworks and AWS Bedrock AgentCore for developing AI agents and workflow orchestration.

• AI Agents & Knowledge Base: Experience developing AI agents for customer query automation and Knowledge Base (KB) solutions.

• Experience with document parsing, chunking, vectorizing and re-ranking strategies.

• Guardrails & Security: Experience configuring AWS Bedrock Guardrails and implementing authentication and authorization for secure AI applications.

• AWS Services: Hands-on experience with API Gateway, Lambda, S3, IAM, CloudWatch, ECR, and SageMaker.

• Software Engineering: Experience with Git, REST APIs, and CI/CD pipelines.

• Relevant AWS certifications (e.g., AWS Certified AI Practitioner, AWS Certified Machine Learning Engineer – Associate, or AWS Certified Solutions Architect – Associate) are a plus.

Good to have skills:

• Hands-on experience with OCR/Document Intelligence engines and NLP techniques for extracting structured information from documents and images.

• Hands-on experience with Bedrock Agentcore

• Hands-on experience with OpenAI, Anthropic, Gemini, or other foundation models.

• Experience with Docker, Kubernetes, and MLOps practices.

• Experience with Redshift, SQL, DynamoDB, or AWS Glue.

• Exposure to model monitoring, evaluation, and observability for GenAI applications.

• Ability to work in an Agile and DevOps environment.