Q

Senior Machine Learning Engineer( Mumbai & Bangalore) (Chennai)

Quantiphi Verified employer

Actively hiring · Posted 8d ago · JEV26108B2DC2FEBA

SalarySalary not disclosed
Experience4–8 yrs
LocationChennai, Tamil Nadu
Work modeHybrid · Full time
Openings1
IndustryIT Services & Consulting

Job description

Quantiphi is an award winning Data Science and Machine Learning Software and Services Company focused on helping organizations translate the big promise of Machine Learning technologies into quantifiable business impact. We were founded on the belief that machine learning and artificial intelligence are transformative technologies that will create the next quantum gain in customer experience and unit economics of businesses. We are one of the five global launch partners for Google in Machine Learning and one of the three global launch partners for Google Cloud Contact Center AI solution.

Our signature approach combines ground-breaking machine-learning research with disciplined cloud and data-engineering practices to create breakthrough impact at unprecedented speed.

Role: Generative AI Engineer

Experience Level: 3.5 - 7 Years

Location: Chennai/ Bangalore/Mumbai

Role Overview

We are looking for a Senior ML Engineer to design, build, and deploy production-grade Agentic AI systems, multi-agent workflows, and MLOps pipelines on GCP. You will work with Googles Gemini Enterprise Agent Platform (GEAP), Agent Development Kit (ADK), and key protocols (MCP, A2A) to deliver enterprise-grade AI solutions.

Key Responsibilities

Agentic AI Development: Design multi-agent workflows using ADK, LangGraph, and Vertex AI Agent Builder.

Integrations & Protocols: Implement tool calling and inter-agent comms using MCP (Model Context Protocol) and A2A.

Retrieval & Knowledge Systems: Build GraphRAG pipelines combining Knowledge Graphs, Vector Search, and Hybrid Search.

AgentOps & State Management: Manage long/short-term agent memory, state handling, and operational monitoring. Technical Skill Requirements

Must Have

Agentic Frameworks: Hands-on experience with ADK, Vertex AI Agent Builder, LangGraph, or LlamaIndex.

Tooling & Protocols: Experience with MCP servers/clients, A2A protocols, function calling, and tool orchestration.

Retrieval Techniques: GraphRAG, Vector Embeddings, Knowledge Graphs, and Hybrid Search. Positive to Have

Domain Knowledge: Healthcare, Life Sciences, Insurance, or Financial Services.

Certifications: GCP Professional Machine Learning Engineer or Cloud Architect. .

Key skills

How to apply

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