Senior Machine Learning Engineer, Drive

The posting, as DoorDash wrote it

About the Team

DoorDash Drive powers deliveries placed through merchants' own channels—including their websites, mobile apps, and phone orders—using DoorDash's logistics network. The Drive Machine Learning team builds the prediction and intelligence systems that power this business, including delivery and pickup time estimation, merchant prep-time prediction, order release optimization, logistics decision-making, and AI-powered delivery quality signals.
Drive presents a unique machine learning challenge. Every merchant has different operational workflows, preparation patterns, and customer expectations, requiring models that generalize across millions of deliveries while adapting to highly diverse merchant behavior. Our team has significant opportunities to improve prediction accuracy, optimize logistics decisions, and build AI-native experiences that directly improve merchant, consumer, and dasher outcomes.

About the Role

As a Machine Learning Engineer on the Drive team, you'll own machine learning systems end-to-end—from feature engineering and model development to experimentation, deployment, monitoring, and continuous iteration.
Your work will span several high-impact problem areas:

• Build next-generation machine learning models for delivery ETA, pickup ETA, merchant prep-time estimation, and order release prediction that improve reliability for merchants and consumers.
• Develop deep learning models that leverage large-scale spatiotemporal, marketplace, and behavioral signals to improve prediction accuracy.
• Apply reinforcement learning and optimization techniques to improve logistics decision-making, assignment strategies, and marketplace efficiency.
• Build AI-native product experiences using large language models (LLMs) and vision-language models (VLMs). For example, transform pickup photos, item verification flows, receipts, and drop-off images into structured quality signals that help verify orders, prevent delivery defects, and improve issue resolution.
• Design and run rigorous online experiments, production monitoring, and model iteration to continuously improve performance.
• Partner closely with software engineers, product managers, data scientists, and platform teams to bring new machine learning capabilities into production at scale.
• You'll have the opportunity to work across traditional machine learning, deep learning, reinforcement learning, optimization, and multimodal AI while solving some of the most challenging logistics problems at DoorDash.

You're excited about this opportunity because...

• You enjoy solving large-scale machine learning problems that directly impact millions of deliveries.
• You have a strong sense of ownership and enjoy taking models from research through production.
• You're comfortable working in ambiguous environments where experimentation and iteration drive product decisions.
• You care about both model quality and production reliability.
• You're excited to work across a di

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success have no place at DoorDash. We value a diverse workforce – people who identify as women, non-binary or gender non-conforming, LGBTQIA+, American Indian or Native Alaskan, Black or African American, Hispanic or Latinx, Native Hawaiian or Other Pacific Islander, differently-abled, caretakers and parents, and veterans are strongly encouraged to apply. Thank you to the Level Playing Field Institute for this statement of non-discrimination.

Pursuant to the San Francisco Fair Chance Ordinance, Los Angeles Fair Chance Initiative for Hiring Ordinance, and any other state or local hiring regulations, we will consider for employment any qualified applicant, including those with arrest and conviction records, in a manner consistent with the applicable regulation.

If you need any accommodations, please inform your recruiting contact upon initial connection.

Notice Regarding Use of AI and Automated Tools: To streamline our hiring process, DoorDash utilizes an automated recruitment tool called Metaview.

How it works: Metaview assists our recruiting team by evaluating job related qualifications and characteristics in connection with hiring. The tool is designed and used to support - rather than replace - human decision-making; trained personnel make final decisions with meaningful human review and oversight, and DoorDash does not use Metaview or other AI-enabled tool in a manner that has the effect of subjecting applicants or employees to discrimination based on any protected characteristic or proxy or for engaging in any protected activity under applicable law.

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