Machine Learning Engineer

1 week ago

Mumbai, Maharashtra, India Fomogo - Hire Fast with AI Full time ₹ 12,00,000 - ₹ 36,00,000 per year

This opening is for Nova (not Fomogo).

While the role is posted via Fomogo's page, you'll be joining the
Nova team
, building AI teammates that help businesses protect revenue, prevent losses, and eliminate repetitive work.

About Nova:

Nova is building AI teammates that help businesses protect revenue, prevent invisible losses, and free teams from repetitive work. We focus on high-impact areas like reconciliations, contract reviews, and compliance tracking; turning manual tasks into ROI-driven automation that empowers people to do their best work.

About the Role

We're looking for an experienced Machine Learning Engineer (MLE)
to lead our ML efforts end-to-end
. This role involves architecting agentic AI workflows and optimizing model pipelines in production. You will own how our AI backbone scales, collaborate with backend and product teams, and ensure our agents are powerful, reliable, cost-efficient, and explainable. This is
a hands-on role
where you will build, guide, mentor, and influence the ML direction at Nova.

Role Responsibilities

  • Architect and scale ML pipelines powering Nova's AI teammates.
  • Implement multi-LLM, multi-agent orchestration
    (e.g.,
    LangGraph
    or equivalents) with routing, chaining, retries, tool-use, guardrails, and persisted state.
  • Design and optimize
    RAG
    pipelines including hierarchical chunking, embeddings, hybrid search, and re-ranking.
  • Build and maintain connectors so agents can reliably discover and integrate with external systems.
  • Deploy and monitor models in production using APIs, tracing, metrics, and balancing cost with performance.

Required Qualifications

  • 4–5 years as an ML Engineer / Applied Scientist working in production environments.
  • Strong Python (FastAPI/Flask), PyTorch/TensorFlow, and data pipeline expertise.
  • Deep knowledge of LLMs, RAG systems, embeddings, and vector DBs (PGVector/Postgres preferred).

Preferred Qualifications

  • Experience working with multiple LLM providers (OpenAI, Anthropic, Google, open-source models) and balancing cost, latency, and quality.
  • Comfortable with Docker, Kubernetes, CI/CD, and deploying to AWS/GCP.

Good to Have

  • Experience with LangGraph/LangChain, vLLM/Ray.
  • Familiarity with LLM evaluation frameworks or event-driven architectures.

What you will get:

A chance to build from 0 to 1 the AI backbone of a product targeting a $100M+ ARR opportunity. End-to-end ownership and visibility, your code will run in production, not in notebooks. A front-row seat to shape how agentic AI gets applied to real-world, high-stakes problems.

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