Machine Learning Engineer, Drive

DoorDash US
San Francisco, Sunnyvale, Seattle
Workplace: OnsiteFull timeUSD 137,100 - 201,600 annuallyFunction: Data Science & Machine LearningExperience: 5+ yearsSkills: ["Ownership","Experimentation","Cross-functional collaboration","Attention to reliability","Comfort in ambiguity"]

Own Drive machine learning systems end-to-end, from feature engineering and model development through experimentation, deployment, monitoring, and iteration. Build next-generation models for delivery ETA, pickup ETA, merchant prep-time, and order release prediction, leveraging large-scale spatiotemporal and behavioral signals. Apply deep learning, reinforcement learning, optimization, and multimodal AI (LLMs/VLMs) to improve prediction accuracy and logistics decision-making at production scale.

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FursaFursa
DoorDash US
DoorDash US
22 hours ago

Machine Learning Engineer, Drive

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Source: Company careers pageValidated by: Fursa AI
Last checked: 3 hours agoStatus: Live

Job Summary

Own Drive machine learning systems end-to-end, from feature engineering and model development through experimentation, deployment, monitoring, and iteration. Build next-generation models for delivery ETA, pickup ETA, merchant prep-time, and order release prediction, leveraging large-scale spatiotemporal and behavioral signals. Apply deep learning, reinforcement learning, optimization, and multimodal AI (LLMs/VLMs) to improve prediction accuracy and logistics decision-making at production scale.
Location: San Francisco, Sunnyvale, Seattle
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Own Drive ML systems end-to-end, including feature engineering, model development, experimentation, deployment, monitoring, and continuous iteration.
  • •Build next-generation ML models for delivery ETA, pickup ETA, merchant prep-time estimation, and order release prediction.
  • •Develop deep learning models using large-scale spatiotemporal, marketplace, and behavioral signals to improve prediction accuracy.
  • •Apply reinforcement learning and optimization techniques to improve logistics decision-making and marketplace efficiency.
  • •Design and run online experiments and production monitoring, and partner with software engineers, product managers, data scientists, and platform teams to scale ML capabilities.

Pay and Benefits

Salary: USD 137,100 - 201,600 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVision401kPaid ParentalPaid Leave

Key Requirements

  • •5+ years of industry experience building and shipping production machine learning systems with measurable business impact.
  • •Strong experience developing production ML models using modern deep learning frameworks such as PyTorch and distributed processing such as Spark and Airflow.
  • •Experience building, deploying, monitoring, and maintaining production ML systems end-to-end.
  • •Strong software engineering skills in Python and experience with modern ML infrastructure and tooling.
  • •Deep expertise in one or more areas such as deep learning, reinforcement learning, optimization/operations research, or LLMs/VLMs.
Experience:5+ years
Skills:OwnershipExperimentationCross-functional collaborationAttention to reliabilityComfort in ambiguity
Languages:English
Tech Stack:Machine LearningPythonPyTorchSparkAirflowReinforcement learningOptimizationLLMsVLMsClaude CodeCodexCursor

Company Brief

DoorDash US
On-demand logistics platform connecting consumers with local restaurants, grocers, and retailers for food delivery, pickup, and convenience services. Operates a marketplace and last-mile delivery network while offering tools and analytics for merchants and couriers.
Industry: Online Marketplaces
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: San Francisco, United States
Founded: 2013
WebsiteLinkedIn