Machine Learning Engineer

About the Company: Fomogo is helping Nova hire! We’re excited to be supporting Nova, a fast-growing AI company building AI teammates that protect revenue, prevent invisible losses, and free teams from repetitive work. They’re tackling high-impact areas like reconciliations, contract reviews, and compliance tracking—turning manual work into ROI-driven automation.

About the Role: Right now, Nova is looking for an experienced Machine Learning Engineer to lead their ML efforts end-to-end.

Responsibilities:

• Architect and scale ML pipelines powering Nova’s AI teammates.
• Implement multi-LLM, multi-agent orchestration (routing, chaining, retries, tool-use, guardrails, persisted state).
• Design and optimize RAG pipelines (hierarchical chunking, embeddings, hybrid search, re-ranking).
• Build and maintain connectors for external system integrations.
• Deploy and monitor models in production with APIs, tracing, and metrics—balancing cost vs performance.

Qualifications:

• ✅ 4–5 years as an ML Engineer / Applied Scientist in production environments.

Required Skills:

• ✅ Strong Python (FastAPI/Flask), PyTorch/TensorFlow, and data pipeline expertise.
• ✅ Deep knowledge of LLMs, RAG systems, embeddings, and vector DBs (PGVector/Postgres preferred).

Preferred Skills:

• ✨ Bonus if you’ve worked with multiple LLM providers (OpenAI, Anthropic, Google, OSS models), or have experience with Docker/Kubernetes, LangGraph/LangChain, or evaluation frameworks.

Pay range and compensation package: Build the AI backbone from 0 → 1 for a product targeting a $100M+ ARR opportunity. End-to-end ownership: your work runs in production, not just notebooks. A front-row seat to shape how agentic AI applies to real-world, high-stakes problems.