quantiphi
Senior Machine Learning Engineer
- Compensation
- Not disclosed
- Location
- IN KA Bengaluru
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 4+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- 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.
Nice to have
- 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.
Full description
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!
JOB ROLE - Senior Machine Learning Engineer (4-7 yrs)
As a Senior Machine Learning Engineer at Quantiphi, you will be responsible for designing and developing advanced machine learning models and algorithms to solve complex business problems. You will work on optimizing and deploying these models on AWS infrastructure, ensuring scalability and reliability.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.