Staff Machine Learning Engineer

Join Evolve's Data Product team as a Staff Machine Learning Engineer. In this hands-on role, you will build and own high-impact ML systems, contribute to economic and pricing work, and mentor other contributors. You will have end-to-end ownership of initiatives and will partner closely with various teams. Benefits include a 401(k) match, free travel credit, and health insurance.

Lead the technical direction and hands-on delivery of prioritized applied machine learning initiatives, translating business opportunities into clear decision frameworks and technical approaches.

Mentor data scientists, raise the team's technical judgment, and create leverage beyond your own projects while remaining hands-on in a lean, remote team.

This is an individual-contributor role for someone who enjoys both modeling and systems work

Marketplace, travel, hospitality, or another domain where models influence high-frequency operating decisions

Responsibilities

• Build and operate machine learning systems end to end, including data and feature pipelines, training and evaluation, batch or online inference, deployment, monitoring, failure handling, and iteration.
• Hands-on experience with modern data and ML infrastructure such as Snowflake, dbt, cloud orchestration, and practical MLOps or model-governance patterns, or comparable technologies and architectures
• Ability to connect technical decisions to business outcomes and communicate tradeoffs clearly to technical, product, business, and executive audiences
• Experience owning production ML systems end to end, including deployment or scoring, monitoring, failure handling, operational support, and iteration after launch

Requirements

• Comfortable working in Git-based development environments with strong software-engineering practices, including code review, automated testing, CI/CD, versioning, and safe production deployment
• Strong applied-statistics judgment, including experimentation or causal-inference fundamentals and the ability to contribute meaningfully to economic, forecasting, or optimization work
• Evidence of Staff-level scope: you have led ambiguous, cross-functional ML or DS work from idea through sustained production use, influenced technical direction across multiple teams or at least 2–3 significant projects, and created durable technical leverage for other contributors
• A self-directed, collaborative working style: you can prioritize across a broad problem space, receive and give direct feedback, influence without formal authority, and remain hands-on in a lean, remote team
• Expert-level Python and SQL skills, including the ability to design, write, test, and maintain production-quality code while working effectively with large and complex datasets
• Typically 8+ years applying machine learning, data science, statistics, or econometrics to consequential business problems
• Expert-level applied modeling and model-evaluation judgment, including selecting appropriate modeling approaches, assessing tradeoffs and limitations, validating model performance, and determining when simpler or more sophisticated methods are appropriate
• An advanced degree in a quantitative field, or equivalent depth demonstrated through applied work
• Demand forecasting, dynamic pricing, revenue management, price-elasticity estimation, econometrics, causal inference, or optimization

Preferred

• NLP, LLM, voice, or other unstructured-data products

Pay

USD 180,000 - 195,000