Senior Machine Learning Engineer

Latitude

India

On-site

INR 1,800,000 - 2,400,000

Full time

3 days ago
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Job summary

Quantiphi is seeking a Senior Machine Learning Engineer to design, develop, and deploy advanced ML models and AI agents. You will work on LangChain-like frameworks, create RAG pipelines, and optimize models for scalable AWS deployments.

You should have strong Python skills, experience with AWS Bedrock, and familiarity with enterprise AI workflows, CI/CD, and security guardrails. Opportunity to influence cutting-edge AI solutions across domains.

Qualifications

  • Experience with LangChain, LangGraph, LlamaIndex, CrewAI, or similar Agentic AI frameworks.
  • Strong Python development and data tooling experience (Pandas, NumPy, FastAPI).
  • Hands-on with AWS Bedrock and foundation models like Claude Haiku/Sonnet.
  • Proficient in building RAG pipelines, prompt engineering, GenAI apps.

Responsibilities

  • Design and develop advanced ML models and algorithms for business use cases.
  • Optimize, deploy and monitor models on AWS infrastructure ensuring scalability.
  • Build AI agents and knowledge-base solutions for customer queries.

Skills

Agentic AI frameworks
Python
AWS Bedrock
LLM & GenAI
ML Pipeline
Agentic AI
AI Agents
Document parsing
Security Guardrails
AWS Services
Software Engineering
AWS Certifications

Tools

Titan Embeddings
OpenSearch Vector Search
REST APIs
Git
CI/CD

Job 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.
  • 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.

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

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