Staff Machine Learning Engineer

EvenUp EvenUp · Vertical AI · San Francisco, CA · Hybrid · Data Science

Staff Machine Learning Engineer at EvenUp, a fast-growing vertical SaaS company using AI to close the justice gap. This role involves setting technical direction for the Piai™ platform, shaping modeling strategy, and building production systems. Responsibilities include tackling complex modeling problems, applying advanced ML techniques, establishing evaluation standards, driving data excellence, and providing technical leadership and mentorship. Requires 7+ years of ML engineering experience with production-shipped models and deep expertise in ML/NLP, particularly LLMs.

What you'd actually do

  1. Set technical strategy for a broad area of the ML roadmap, translating ambiguous business and research goals into scoped, production-ready systems.
  2. Tackle the hardest modeling problems in the org - complex reasoning, long-context and multi-document understanding, or other frontier challenges as they come up.
  3. Apply advanced ML techniques - fine-tuning, reinforcement learning, retrieval, or others - and know when a technique is the right tool versus over-engineering.
  4. Establish rigorous evaluation standards, reducing hallucinations, improving factual consistency, and defining what "good" looks like for a given system.
  5. Drive data excellence through hands-on analysis of training and evaluation data, managing noise, edge cases, and drift at scale.

Skills

Required

  • Python
  • modern ML/NLP frameworks
  • LLMs
  • ML engineering
  • NLP
  • setting technical strategy
  • mentoring engineers
  • Product and Engineering leadership partnership

Nice to have

  • PhD in Machine Learning, Computer Science, or a related quantitative field
  • document understanding
  • entity/relationship extraction
  • structured extraction from unstructured text
  • LLM fine-tuning techniques (LoRA, QLoRA, RLHF/RLVR)
  • advanced prompt engineering
  • high-growth startup environment

What the JD emphasized

  • production systems
  • production-ready systems
  • shippable systems
  • models shipped and running in production
  • rigorous evaluation standards
  • evaluation data
  • technical strategy
  • set strategy
  • technical direction

Other signals

  • Staff ML Engineer role
  • technical leadership
  • setting technical direction
  • shaping modeling strategy
  • production systems
  • mentoring senior engineers
  • driving decisions
  • translating ambiguous business and research goals into scoped, production-ready systems
  • tackle the hardest modeling problems
  • complex reasoning
  • long-context and multi-document understanding
  • frontier challenges
  • apply advanced ML techniques
  • fine-tuning
  • reinforcement learning
  • retrieval
  • rigorous evaluation standards
  • reducing hallucinations
  • improving factual consistency
  • defining what 'good' looks like
  • drive data excellence
  • hands-on analysis of training and evaluation data
  • managing noise, edge cases, and drift at scale
  • technical leadership and mentorship
  • raising the bar for experimentation, benchmarking, and engineering rigor
  • bridge between research and production
  • ensuring new techniques get integrated into shippable systems
  • partner cross-functionally
  • cost effectively scale practical machine learning systems
  • hyper-growth environment
  • 7+ years of hands-on ML engineering experience
  • multiple models shipped and running in production
  • Deep expertise in ML and NLP, including LLMs
  • track record of solving hard modeling problems
  • High proficiency in Python
  • strong command of modern ML/NLP frameworks
  • Demonstrated ability to set technical strategy and drive execution
  • ambiguous, fast-moving environments
  • track record of mentoring engineers and raising technical standards
  • Experience partnering directly with Product and Engineering leadership