Machine Learning Engineer

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 delivery service quality for DoorDash's three-sided marketplace of consumers, merchants, and dashers. DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last-mile logistics in the long term. We are looking for Machine Learning Engineers, Economists, Mathematicians, Statisticians, and Senior Quantitative Researchers from all disciplines.

As a Machine Learning Engineer, you will have the opportunity to leverage our robust data and machine learning infrastructure to develop inference and 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.

• Build statistical and ML models that run in production to help enhance the consumer experience by reducing missing and incorrect items, cancellations, estimated arrival times, and non-fulfilled orders.
• Own the modeling life cycle end-to-end including feature creation, model development and prototyping, experimentation, monitoring and explainability, and model maintenance.
• Be exposed to new opportunities where delivery quality can be used as a lever for demand shaping, search ranking, customer segmentation, etc.

• High-energy and confident - you keep the mission in mind, take ideas and help them grow using data and rigorous testing, show evidence of progress and then double down.
• You're an owner - driven, focused, and quick to take ownership of your work.
• Humble - you're willing to jump in and you're open to feedback.
• Adaptable, resilient, and able to thrive in ambiguity - things change quickly in our fast-paced startup and you'll need to be able to keep up.
• Growth-minded - you're eager to expand your skill set and excited to carve out your career path in a hyper-growth setting.
• Desire for impact - ready to take on a lot of responsibility and work collaboratively with your team.

• 3+ years of industry experience post PhD or 5+ years of industry experience post graduate degree of developing machine learning models with business impact.
• M.S., or PhD. in Machine Learning, Statistics, Computer Science, Applied Mathematics or other related quantitative fields.
• Demonstrated expertise with programming languages, eg python, SciKit Learn, Lightgbm, Spark MLLib, PyTorch, TensorFlow, etc.
• Deep understanding of complex systems such as Marketplaces, and domain knowledge in two or more of the following: Machine Learning, Causal Inference, Operations Research, Forecasting and Experimentation.
• Experience of shipping production-grade ML models and optimization systems, and designing sophisticated experimentation techniques.
• You are located or are planning to relocate to San Francisco, CA, Sunnyvale, CA.

At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users-from Dashers to merchant partners to consumers. We are a technology and logistics company that started with door-to-door delivery, and we are looking for team members who can help us go from a company that is known for delivering food to a company that people turn to for any and all goods.

We're committed to growing and empowering a more inclusive community within our company, industry, and cities. That's why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.