About the role
EvenUp is on a mission to close the justice gap using technology and AI. We empower personal injury lawyers and victims to get the justice they deserve. Our products enable law firms to secure faster settlements, higher payouts, and better outcomes for victims injured through no fault of their own in vehicle collisions, accidents, natural disasters, and more. We are one of the fastest-growing vertical SaaS companies in history, and we are just getting started. EvenUp is backed by top VCs, including Bessemer Venture Partners, Bain Capital Ventures, SignalFire, and Lightspeed. We are looking to expand our team with talented, driven, and collaborative individuals who seek to have a lasting impact. Learn more at www.evenuplaw.com . 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. What You Bring 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.
