Evolve - Staff Machine Learning Engineer
Requirements
• Snowflake, dbt, feature stores, model registries, workflow orchestration, and practical MLOps or model-governance patterns. • LLM evaluation, retrieval-augmented generation, agents, or cost and latency optimization for LLM products in production. • Demand forecasting, dynamic pricing, revenue management, price-elasticity estimation, causal inference, or optimization. • Marketplace, travel, hospitality, or another domain where models influence high-frequency operating decisions. • Standing up ML infrastructure or platform patterns at a company that did not have them yet. • An advanced degree in a quantitative field, or equivalent depth demonstrated through applied work.
Responsibilities
• Lead the technical direction and hands-on delivery of one or two prioritized applied ML initiatives at a time. • Translate business opportunities into clear decision frameworks, technical approaches, success measures, and plans for adoption and impact evaluation. • Build and operate ML systems end to end, including data and feature pipelines, training and evaluation, batch or online inference, deployment, monitoring, failure handling, and iteration. • Contribute directly to forecasting, demand and price-elasticity estimation, causal measurement, and optimization work that supports pricing and revenue decisions. • Design and analyze experiments and quasi-experiments to evaluate product, model, and policy changes. • Establish reusable standards for testing, reproducibility, versioning, observability, documentation, and responsible model operation; review designs and code across the team. • Partner with Product, Engineering, Data Engineering, Revenue Management, and other business owners to make technical tradeoffs and integrate models into products and operating workflows. • Mentor data scientists, raise the team's technical judgment, and create leverage beyond your own projects while remaining hands-on. • What makes you a great fit • Typically 8+ years applying machine learning, data science, statistics, or econometrics to consequential business problems. • 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. • 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. • 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. • Experience owning production ML systems end to end, including deployment or scoring, monitoring, failure handling, operational support, and iteration after launch. • 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. • Strong applied-statistics judgment, including experimentation or causal-inference fundamentals and the ability to contribute meaningfully to economic, forecasting, or optimization work. • Comfortable working in Git-based development environments with strong software-engineering practices, including code review, automated testing, CI/CD, versioning, and safe production deployment. • Ability to connect technical decisions to business outcomes and communicate tradeoffs clearly to technical, product, business, and executive audiences. • 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.
Benefits
• Evolve's Data Product team builds data and machine-learning products that improve owner acquisition and retention, pricing, revenue performance, and how teams make decisions. We're hiring a hands-on Staff Machine Learning Engineer with applied data science depth to build and own the highest-impact ML systems across that portfolio. • You'll turn ambiguous opportunities into durable production systems: frame the problem and success measures, develop and validate models, build the pipelines and inference patterns needed to run them, integrate them into products or workflows, and measure adoption and business impact. You'll also contribute directly to our economic and pricing work, including forecasting, demand and price-elasticity estimation, causal measurement, and optimization. • This is an individual-contributor role for someone who enjoys both modeling and systems work. You'll set technical direction and pragmatic engineering standards for a lean data science team, mentor other contributors, and partner closely with Product, Engineering, Data Engineering, Revenue Management, and business leaders. The exact mix of initiatives will shift with company priorities, but end-to-end ownership and measurable business use will remain constant. This role reports to the head of Data Product. • Annual base salary range: $180,000–$195,000, depending on relevant experience. This role is also eligible for equity and a variable annual bonus based on both company and individual performance. • Location • All Evolve team members must live in one of our approved locations by their first day. We can hire from anywhere in the U.S. except D.C. and Hawaii. Some positions may also have restrictions based on compensation in the following states: California, Maryland, New York, Pennsylvania, Rhode Island, and Washington. If you live in Colorado, you can work remotely anywhere in the state, at our downtown Denver office, or a hybrid of both! If you're planning to move soon, please let us know, and we'll be happy to review your application again. • California Applicant Privacy Policy | Evolve • How we reward Evolvers • We’re intentional about offering benefits that empower every Evolver to thrive both professionally and personally because they’re more than perks—they’re investments in our customer-obsessed, high-performing team. • We believe in treating others as they want to be treated, providing benefits that deliver real value, and challenging the status quo to meet the diverse needs of our team. Whether it’s helping you take care of your health, plan for the future, or celebrate life’s milestones, our offerings are designed to support you every step of the way. • Financial Wellness: Industry-competitive pay, equity in the company, and a 401(k) with a 4% immediate vesting match. • Financial Wellness: • Family Support: 16-18 weeks of paid parental leave for birthing parents and 10 weeks for non-birthing parents, plus infertility coverage. • Family Support: • Health & Wellness: Comprehensive medical, dental, and vision plans, with 100% employer-paid dental and vision for individual coverage, a low-cost medical option, 10 free mental health visits, and pet insurance. • Health & Wellness: • Time to Recharge: Generous PTO, RTO (for full-time exempt employees), sick leave, holidays, and a personal holiday to celebrate what matters most to you. • Time to Recharge: • Travel Perks: Annual Evolve travel credit after one year and discounts on stays at all Evolve properties. • Growth Opportunities: World-class onboarding programs, learning, and development resources to help you grow your impact. • Growth Opportunities: • Connection: Employee Resource Groups celebrating our diverse communities at Evolve. • Connection: • How we work together • With our core values as our guide, every Evolver helps shape the company we want to work for and the people we want to be. We’ve cultivated a culture of collaboration, care, and responsibility that we can all be proud of, and we’re excited to see what you’ll bring as your authentic self. • Still curious about who we are and what we do? Read more about our business and our culture at evolve.com.
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