[Hiring] Staff Machine Learning Engineer @EvenUp

Role Description

Join EvenUp as a Staff Machine Learning Engineer and help set the technical direction for how machine learning powers Piai™, our proprietary claims-intelligence platform. This is a technical leadership role - you'll shape modeling strategy across a broad problem space, turning raw legal and medical data into production systems that improve outcomes for personal-injury clients.

You'll partner closely with Product, Research, and Engineering leaders to set strategy, and you'll be a technical anchor for the broader ML team - setting standards, mentoring senior engineers, and driving decisions that shape both product outcomes and company growth.

What You'll Do

• 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.

Qualifications

• 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.

Nice to Have

• 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.

Benefits

• Choice of medical, dental, and vision insurance plans for you and your family.
• Additional insurance coverage options for life, accident, or critical illness.
• Flexible paid time off, sick leave, short-term and long-term disability.
• 10 US observed holidays, and Canadian statutory holidays by province.
• A home office stipend.
• 401(k) for US-based employees and RRSP for Canada-based employees.
• Paid parental leave.
• A local in-person meet-up program.
• Hubs in San Francisco and Toronto.