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DoorDash

Runs apps for local food and grocery delivery

Senior Software Engineer - ML Serving Platform

Applied Machine LearningPosted on Nov 12
Full-timeIn-person

About the Job

Requirements

  • You have 6+ years of software engineering experience designing, building, and operating production infrastructure or distributed systems.
  • You have hands-on experience serving large or complex neural models online, with accountability for latency, availability, and resource efficiency.
  • You bring strong distributed systems fundamentals and proficiency in a backend or systems language such as Python, Go, Java, Kotlin, or C++.
  • You understand inference tradeoffs across batching, concurrency, caching, memory, and CPU/GPU utilization, and can diagnose production bottlenecks.
  • You have operated services on Kubernetes or comparable infrastructure, including resource configuration, autoscaling, and failure recovery.
  • You hold a degree in Computer Science or a related field, or have equivalent practical experience.

Responsibilities

  • Lead projects from customer problem through design, implementation, and rollout. Coordinate delivery across engineers, mentor peers, and help shape the team’s roadmap.
  • Improve inference performance through production traces, load tests, and CPU/GPU profiling. Work with model owners to balance model quality, tail latency, throughput, and cost.
  • Partner with Compute on capacity, placement, and scaling, accounting for request complexity, cache state, GPU memory, and model startup behavior.
  • Build self-serve APIs and deployment workflows that manage models, runtime dependencies, features, and versioned state, with validation, safe rollout, and rollback.
  • Evaluate, integrate, and extend open source tools and vendor capabilities that advance model serving. Decide when to build or adopt, and collaborate with maintainers and vendors.
  • Own production reliability through service objectives, observability, on-call, incident response, and follow-through. Reduce recurring operational work through automation.

Desired Qualifications

  • Experience integrating or extending inference tools such as Triton Inference Server or PyTorch.
  • Experience with multi-GPU inference, model parallelism, model-aware caching, or accelerator scheduling.
  • Experience building model workflows, deployment tooling, or instrumentation with Metaflow, Helm, or OpenTelemetry.

About the Company

DoorDash

Runs apps for local food and grocery delivery

DoorDash runs apps that let people order restaurant meals, groceries, and other goods from local businesses, which independent couriers called Dashers bring to their doors. In 2019 it overtook Grubhub to become the largest food delivery service in the United States, and it later expanded abroad by buying Finland's Wolt and Britain's Deliveroo. Merchants pay DoorDash a fee on each order and can buy ads in its apps, while customers pay delivery and service fees or join DashPass, a subscription that cuts those fees. Businesses can also hire Dashers through its Drive service to carry orders placed on their own websites. Four Stanford students founded DoorDash in 2013, and it is based in San Francisco, California.

Company size
10,001+
Company stage
IPO
Headquarters
San Francisco, CA
Founded
2013

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