Machine Learning Engineer

Evoke HR; Hyderabad, Bengaluru; Hybrid; INR 4,200,000 - 7,200,000; Full time

Job summary

Evoke HR is seeking a Senior Data / ML Engineer to build and scale production-ready AI systems. The role is hands-on and engineering-heavy, focused on moving AI from prototype to governed, reliable production. You will deploy LLM-powered apps, design RAG pipelines, and ensure cost-efficient, observable architectures.

You will collaborate with product, platform, and governance teams to deliver responsible AI within enterprise environments, advancing multi-agent workflows and scalable ML pipelines.

Qualifications

• 6+ years of experience in Data Engineering, ML Engineering, or Applied AI.
• Hands-on experience deploying LLM-based systems in production.
• Strong Python skills and experience with scalable systems.
• Experience with agent frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or similar).
• Solid understanding of RAG, vector databases, embeddings, and prompt optimization.
• Familiarity with MLOps, monitoring, and cost/performance trade-offs.

Responsibilities

• Build and deploy LLM-powered applications and agentic workflows (single & multi-agent).
• Design and implement RAG pipelines, embeddings, and vector search.
• Develop end-to-end ML/LLM pipelines from data ingestion to inference and monitoring.
• Productionize AI systems with cost controls, observability, and guardrails.
• Integrate AI solutions into enterprise workflows and platforms.
• Collaborate with product, platform, and governance teams to deliver responsible AI.

Skills

Python

Production ML

LLM deployment

Agent frameworks

RAG knowledge

MLOps

Cost/performance trade-offs

Tools

LangChain

LlamaIndex

AutoGen

CrewAI

Job description

Were hiring a Senior Data / ML Engineer to build and scale production-grade AI and agentic systems that solve real business problems. This role is hands‑on and engineering‑heavy, focused on taking AI from prototype to reliable, governed production systems.

What You’ll Do

Build and deploy LLM-powered applications and agentic workflows (single & multi-agent).

Design and implement RAG pipelines, embeddings, and vector search.

Develop end-to-end ML/LLM pipelines from data ingestion to inference and monitoring.

Productionize AI systems with cost controls, observability, and guardrails.

Integrate AI solutions into enterprise workflows and platforms.

Collaborate with product, platform, and governance teams to deliver responsible AI.

Required Skills and Qualifications:

6+ years of experience in Data Engineering, ML Engineering, or Applied AI.

Hands‑on experience deploying LLM-based systems in production.

Strong Python skills and experience with scalable systems.

Experience with agent frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or similar).

Solid understanding of RAG, vector databases, embeddings, and prompt optimization.

Familiarity with MLOps, monitoring, and cost/performance trade-offs.