Staff ML Engineer: End-to-End ML Systems for Pricing & Growth

Evolve; United States; Hybrid; USD 180,000 - 195,000; Full time

Benefits offered by this job

Financial Wellness

Family Support

Health & Wellness

Time to Recharge

Growth Opportunities

Connection

Job summary

Evolve is seeking a Staff Machine Learning Engineer to own high-impact ML systems across pricing, demand forecasting, and owner acquisition. You will shape problem framing, validate models, build end-to-end pipelines, and measure business impact.

You’ll mentor data scientists, set standards for testing and governance, and partner with Product, Engineering, and Revenue Management to deploy models in real-world workflows while staying hands-on in a lean, remote-enabled team.

Qualifications

• 8+ years applying ML, data science, statistics, or econometrics to business problems.
• Evidence of Staff-level scope across multiple teams or projects.
• Strong Python and SQL production coding and data handling.
• Experience owning production ML systems end to end.
• Familiar with modern data infra and governance patterns.

Responsibilities

• Lead the technical direction and hands-on delivery of one or two applied ML initiatives.
• Translate business opportunities into decision frameworks and adoption plans.
• Build and operate ML systems end to end, from data pipelines to deployment.
• Contribute to forecasting, demand estimation, and pricing optimization work.
• Design experiments and quasi-experiments to evaluate impact.
• Establish testing, observability, versioning, and reproducibility standards.
• Collaborate with Product, Engineering, Data Engineering, and Revenue teams.
• Mentor data scientists and raise the team's technical judgment.

Skills

Python

SQL

Production ML

MLOps

Experimentation

Causal inference

Education

Advanced degree in quantitative field

Tools

Snowflake

dbt

Cloud orchestration

Model governance

Job description

Evolve is seeking a Staff Machine Learning Engineer to own high-impact ML systems across pricing, demand forecasting, and owner acquisition. You will shape problem framing, validate models, build end-to-end pipelines, and measure business impact.

You’ll mentor data scientists, set standards for testing and governance, and partner with Product, Engineering, and Revenue Management to deploy models in real-world workflows while staying hands-on in a lean, remote-enabled team.