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EvenUp

Staff Machine Learning Engineer

EvenUp

Staff Machine Learning Engineer at EvenUp managing ML strategies for claims-intelligence platform. Collaborating with teams to optimize outcomes for personal-injury clients using AI.

Posted 7/8/2026full-timeSan Francisco • California • 🇺🇸 United StatesLead💰 $212,000 - $301,000 per yearWebsite

Tech Stack

Tools & technologies
Python

About the role

Key responsibilities & impact
  • 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

What you’ll need
  • 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.

Benefits

Comp & perks
  • 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.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools
Machine LearningNatural Language ProcessingFine-TuningReinforcement LearningModeling Problem SolvingData AnalysisModel DeploymentEvaluation StandardsLLMsBenchmarking
Soft Skills
MentorshipCross-Functional CollaborationStrategic ThinkingExecution in Ambiguity