Job Openings For machine Learning in Chennai

Ontime Global; Chennai; On-site; INR 4,500,000 - 6,500,000; Full time

Job summary

Ontime Global seeks a senior ML/GenAI engineer in Chennai with 10+ years in software or platform engineering and 3+ years shipping ML/GenAI in production. You will design scalable AI infrastructure, implement RAG, tool calling, MCP, and multi-agent patterns, and work across engineering, security, and compliance teams.

Qualifications include a B.E./B.Tech/M.Tech/M.Sc in CS or related field, strong cloud architecture on AWS/Azure/GCP, experience with AI governance, evaluation, observability, and

Qualifications

• 10+ years in software or platform engineering with ML/GenAI production experience.
• B.E./B.Tech./M.Tech./M.Sc in CS or related field.
• Deep hands-on with LLM patterns: RAG, tool calling, MCP, multi-agent.
• Cloud architecture across AWS/Azure/GCP for scalable AI infra.

Skills

LLM systems experience

Cloud architecture

AI governance & risk

AI evaluation & observability

Policy documentation

Cross-functional collaboration

Education

B.E./B.Tech./M.Tech/M.Sc in CS or related field

Tools

RAG

Tool calling

MCP

Multi-agent frameworks

Job description

Machine Learning

7+Yrs

10+Yrs

Chennai

• B.E. / B.Tech / M.Tech / M.Sc. in Computer Science, Software Engineering, Artificial Intelligence, or a related discipline.
• 10+ years in software or platform engineering, with at least 3+ years shipping ML or GenAI systems in production environments.
• LLM Systems: Deep hands-on experience with LLM application patterns including RAG, tool calling, MCP, and multi-agent frameworks in production.
• Cloud Architecture: Strong proficiency with cloud platforms (AWS, Azure, or GCP); experience designing scalable, secure AI infrastructure and enterprise AI gateways.
• AI Evaluation & Observability: Proven experience with LLM evaluation frameworks, guardrail design, AI security risks, and model observability tooling.
• Exceptional written and verbal communication skills; demonstrated ability to produce clear policy and technical documentation and work across engineering, legal, compliance, and security teams.
• AI Governance & Risk: Experience building responsible AI frameworks, conducting agent risk analyses, managing use-case inventories, and running AI audits.
• Strong analytical and strategic thinking; ability to define standards and reference architectures that balance innovation with governance and safety.