Machine Learning Engineer - ETA & Routing

About the Team We are building the world’s most reliable on-demand logistics engine for delivery and are hiring a Machine Learning Engineer to develop and improve ETA and Routing models within DoorDash’s marketplace. About the Role As a Machine Learning Engineer you will leverage our data and ML infrastructure to build inference and optimization ETA and Routing models that impact millions of users. You’ll work with data scientists, engineers, and product managers to iterate on models that grow the business and improve service quality for our customers. Key Responsibilities Build Deep Learning models for next‑generation ETA that provide accurate, scalable, and robust time predictions. Build Machine Learning models in the routing space to serve as a single source of truth across internal teams. Own the end‑to‑end modeling life cycle—including feature creation, model development and testing, experimentation, monitoring, explainability, and model maintenance. Explore opportunities to use ETA/Routing as a lever for new business, markets, and regions. Learn more through our ML blog posts. Qualities & Experience High‑energy, confident, mission‑focused, and data‑driven. Owner mindset—driven, focused, and quick to take responsibility. Humble and open to feedback. Adaptable, resilient, and able to thrive in ambiguity. Growth‑mindset and eager to expand skill set. Desire for impact and collaboration. Experience 1+ years of industry experience post PhD or 3+ years post graduate degree developing advanced machine‑learning models with business impact. M.S. or Ph.D. in Computer Science, Statistics, or related quantitative fields. Strong background in Deep Learning and open‑source ML technologies such as Spark, PyTorch, Airflow. Proficiency in Python and machine‑learning libraries (LightGBM, Spark MLlib, PyTorch). Deep understanding of complex systems such as marketplaces and domain knowledge in Deep Learning, Reinforcement Learning, Operations Research, or Forecasting. Experience shipping production‑grade ML models and optimization systems and designing sophisticated experimentation techniques. Located or planning to relocate to San Francisco, CA, Sunnyvale, CA, or Seattle, WA. Compensation and Benefits The base salary range for this position is $140,100 – $210,100 USD depending on location. Compensation is also influenced by skills, experience, and work location. Developers who can work remotely receive a localized salary. In addition to base salary, the package includes equity grants. Benefits include healthcare, 401(k) plan with employer match, disability coverage, life insurance, wellness benefits, paid time off, paid parental leave, paid holidays, and more. Equal Opportunity Statement We are committed to growing and empowering an inclusive community. No employee or applicant will face discrimination or harassment based on race, color, ancestry, national origin, religion, age, gender, marital/domestic partner status, sexual orientation, gender identity or expression, disability status, or veteran status. We also consider qualified applicants with arrest and conviction records in compliance with applicable regulations. Accommodation Request If you need any accommodations, please inform your recruiting contact upon initial connection. #J-18808-Ljbffr