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”.