Machine Learning Engineer, Forecast Platform

About the Team

Come help us build the world's most reliable on-demand, logistics engine for delivery! We are bringing on a talented Machine Learning Engineer to help us improve the operational efficiency of DoorDash's three-sided marketplace of consumers, merchants, and dashers. The Forecasting Platform provides a unique opportunity to have a broad impact on the business ensuring we can quickly respond to a rapidly changing operational environment. The team supports projects across all of our major pillars (e.g. supply / demand, auto-scaling infrastructure, support optimization) as well as the development of an internal decision platform for time series.

About the Role

As a Machine Learning Engineer, you will have the opportunity to leverage our robust data and machine learning infrastructure to develop ML models that impact millions of users across our three audiences and tackle our most challenging business problems. You will work with other engineers, analysts, and product managers to develop and iterate on models to help us grow our business and provide the best service quality for our customers.

You're excited about this opportunity because you will…

• Build time-dependent statistical and ML models that solve product needs across our verticals - e.g. matching supply / demand, predicting support needs, providing insights to our internal platforms (ads, experiments, merchant), auto-scale infrastructure and optimize business processes such as promotions

• Own the modeling life cycle end-to-end including feature creation, model development and prototyping, experimentation, monitoring and explainability, and model maintenance

• Contribute to the development of our in-house Forecasting Self-Service Platform and proprietary Forecasting Repository to uplevel our capabilities

• Research new tools within the Forecasting space (e.g. TimeGPT, LLM extensions)

• You can find out more on our ML blog post