Machine Learning Engineer, Forecast Platform

DoorDash is seeking a Machine Learning Engineer to join their Forecast Platform team, working on building the world's most reliable on-demand logistics engine for delivery. This role offers a unique opportunity to impact DoorDash's three-sided marketplace of consumers, merchants, and dashers through advanced machine learning solutions.

The position involves developing sophisticated time-dependent statistical and ML models that directly influence critical business operations, including supply/demand matching, support optimization, and platform insights. You'll work with a robust data and machine learning infrastructure, affecting millions of users across different audience segments.

As a Machine Learning Engineer, you'll own the complete modeling lifecycle, from feature creation to production deployment. The role requires expertise in ML libraries and frameworks, with a focus on building scalable forecasting solutions. You'll contribute to DoorDash's proprietary Forecasting Self-Service Platform and research cutting-edge tools in the forecasting space.

The ideal candidate should have either an M.S. with 3+ years of experience or a PhD with 1+ year of experience in developing production ML models. Strong programming skills, particularly in Python and ML frameworks, are essential. Deep understanding of marketplace dynamics and domain expertise in areas like Machine Learning, Causal Inference, and Operations Research is required.

DoorDash offers competitive compensation with base salary ranging from $137,100 to $299,300 USD, depending on level and location, plus equity opportunities. The company provides comprehensive benefits including medical/dental/vision insurance, 401(k) matching, generous parental leave, and wellness programs. This role offers the chance to work with a fast-growing technology company that's transforming local economies through innovative logistics solutions.