Staff Machine Learning Engineer

EvenUp is on a mission to close the justice gap using technology and AI. The Staff Machine Learning Engineer will set the technical direction for machine learning solutions in the company's claims-intelligence platform, collaborating closely with various teams to drive product outcomes and company growth.

Responsibilities:

• Set technical strategy for a broad area of the ML roadmap, translating ambiguous business and research goals into scoped, production-ready systems
• Tackle the hardest modeling problems in the org - complex reasoning, long-context and multi-document understanding, or other frontier challenges as they come up
• Apply advanced ML techniques - fine-tuning, reinforcement learning, retrieval, or others - and know when a technique is the right tool versus over-engineering
• Establish rigorous evaluation standards, reducing hallucinations, improving factual consistency, and defining what "good" looks like for a given system
• Drive data excellence through hands-on analysis of training and evaluation data, managing noise, edge cases, and drift at scale
• Provide technical leadership and mentorship across the ML team, raising the bar for experimentation, benchmarking, and engineering rigor
• Act as the bridge between research and production - ensuring new techniques get integrated into shippable systems, not just proofs of concept
• Partner cross-functionally with product, engineering, and legal subject-matter experts to set technical direction
• Cost effectively scale practical machine learning systems in a hyper-growth environment, ensuring they remain grounded in real business and customer needs

Requirements:

• 7+ years of hands-on ML engineering experience, with multiple models shipped and running in production
• Deep expertise in ML and NLP, including LLMs, with a track record of solving hard modeling problems - not just applying existing recipes
• High proficiency in Python and strong command of modern ML/NLP frameworks
• Demonstrated ability to set technical strategy and drive execution in ambiguous, fast-moving environments
• A track record of mentoring engineers and raising technical standards beyond your own output
• Experience partnering directly with Product and Engineering leadership, not just executing their asks
• PhD in Machine Learning, Computer Science, or a related quantitative field
• Experience with document understanding, entity/relationship extraction, or structured extraction from unstructured text
• Experience with LLM fine-tuning techniques (LoRA, QLoRA, RLHF/RLVR) or advanced prompt engineering
• Experience in a high-growth startup environment
• Open to remote candidates or 3 days a week hybrid from our Toronto or San Francisco hubs