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

Core Competencies

Role fit

Core Competencies

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Demonstrates deep expertise in Machine Learning and Natural Language Processing, with a strong focus on developing and deploying production-ready systems. Proven ability to set technical strategy, mentor teams, and drive data excellence in fast-paced environments.

Highest-signal resume keywords

Machine Learning EngineeringNatural Language ProcessingPython ProgrammingTechnical LeadershipModel Evaluation Standards

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningNatural Language ProcessingFine-TuningReinforcement LearningModeling Problem SolvingData AnalysisModel DeploymentEvaluation StandardsLLMsBenchmarking

Soft Skills

MentorshipCross-Functional CollaborationStrategic ThinkingExecution in Ambiguity

Tools & Technologies

ML FrameworksNLP Frameworks

Industry Keywords

Technical StrategyProduction SystemsData ExcellenceHyper-Growth Environment

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.