Machine Learning Engineer - Delivery Excellence

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. As a fundamental area of investment for DoorDash, Delivery Excellence has among the coolest problems to solve at scale and creates a major impact on the company and our customers.

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.

Key Responsibilities: • Build statistical and ML models that run in production to help enhance the consumer experience by reducing cancellations, pickup waiting times, delivery lateness, missing and incorrect items 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 • Being exposed to new opportunities where delivery quality can be used as a lever for demand shaping, search ranking, customer segmentation, etc • Mentor and uplevel a talented team of ML Engineers

Requirements: • 1+ years of industry experience post PhD or 3+ 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, e.g. 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 • Located or planning to relocate to San Francisco, CA, Sunnyvale, CA, or Seattle, WA

DoorDash offers competitive compensation, equity grants, comprehensive benefits, and opportunities for growth and impact in a fast-paced startup environment.