Staff Machine Learning Engineer

Role Overview

Join EvenUp as a Staff Machine Learning Engineer to design and architect high-impact generative AI products. You will lead the technical strategy and roadmap for a proprietary claims-intelligence platform, working on complex legal document workflows.

Key Missions / Responsibilities

• Lead ML system design and architecture for large-scale ML systems, with a focus on Retrieval-Augmented Generation (RAG), vector search, and fine-tuning frameworks.
• Define and drive technical strategy and best practices for ML system design, including:
  • embedding pipelines
  • evaluation frameworks
• Mentor and guide ML engineers, promoting technical excellence and continuous growth.
• Bridge applied ML research and production engineering through effective communication.

Requirements

• Strong modern ML engineering experience with:
  • Python
  • PyTorch
  • Vector databases (e.g., Pinecone, Milvus, FAISS)
• Deep expertise in Machine Learning, NLP, LLMs, and generative AI; hands-on experience taking complex systems to production.
• Demonstrated mentorship and ability to represent the ML team in cross-org architectural reviews.
• PhD in Machine Learning, Computer Science, or another quantitative field.
• Excellent communication skills.

Nice-to-haves

• Familiarity with retrieval frameworks such as LangChain or LlamaIndex (or custom retrieval pipelines).
• Strong alignment with EvenUp’s mission around fairness and accessibility in the legal domain.

Work Location / Policy

• Hybrid work from an office hub in Toronto or San Francisco (also listed as “Full remote,” but the profile explicitly calls out hybrid from those hubs).