Staff Machine Learning Engineer

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.

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.

Notice to Candidates

We only post open roles on our career page (evenuplaw.com/careers) or reputable job boards like our official LinkedIn or Indeed pages, and all official EvenUp recruitment emails will come from the domains @evenuplaw.com, @evenup.ai, @ext-evenuplaw.com, no-reply@ashbyhq.com or no-reply@canditech.io. To ensure fairness and proper consideration, we do not accept resumes or expressions of interest via email or social media messages. If you’re interested in a role, please submit your application directly through our careers page.

If you receive communication from someone you believe is impersonating EvenUp, please report it to us at talent-ops-team@evenuplaw.com. Examples of fraudulent domains include “careers-evenuplaw.com” and “careers-evenuplaws.com”.

Benefits & 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.

Equal Opportunity Employer

We are committed to diversity and inclusion in our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Career Page

To apply for this role, please visit our career page.