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DoorDash USA

Software Engineer, Machine Learning Infrastructure - Generative AI

DoorDash USA · San Francisco, CA; Sunnyvale, CA; Seattle, WA

Posted about 3 months ago

or apply directly on DoorDash USA's site. We never take the application ourselves.

Is this posting real?

This role has been open
81 days
DoorDash USA's roles stay open a median of 81 days
Reposted
No
Salary listed
No
0% of DoorDash USA's roles list one
Ghost-job risk at DoorDash USA
high
456 stale, 8 reposted of 462 open
Hiring momentum
682 roles opened in the last 90 days
↑ up vs. the prior 90 days
Last confirmed on the employer's board
2026-10-23

Measured from postings appearing on and disappearing from DoorDash USA's own greenhouse board since 2026-08-03. Full hiring picture for DoorDash USA.

About this role

In this role, you will be part of a small team focused on building production infrastructure for Generative AI at DoorDash. Your responsibilities will include developing and maintaining the evals and LLM observability platform, designing scalable systems for evaluation workflows, and collaborating with various teams to enhance the quality and efficiency of AI-powered products. You will also work on integrating emerging GenAI capabilities into the platform, ensuring high standards for performance and operational excellence.

Our read on this posting3.0out of 5
benefits
5/5
freshness
1/5
career value
4/5
role clarity
5/5
pay transparency
0/5

Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of DoorDash USA as an employer.

What you need

  • B.S., M.S., or PhD. in Computer Science or equivalent
  • 3+ years of industry experience in software engineering
  • Strong backend engineering fundamentals, especially in Python and distributed systems
  • Experience building production services, APIs, data pipelines, or ML infrastructure at scale
  • Experience operating systems in production, including observability, debugging, reliability, incident response, and performance/cost optimization
  • Hands-on experience with evaluation, LLM observability, or measurement systems for ML/LLM products in production

Nice to have

  • Depth in evaluation methodology — LLM-as-judge design and calibration, judge/eval drift detection, human-in-the-loop labeling, or eval harness design for agents and multi-step systems
  • Experience with LLM observability and tracing (e.g., OpenTelemetry, trace/score ingestion) and building instrumentation SDKs
  • Experience building and deploying AI agents or MCP servers in production, including agent evaluation or simulation
  • Experience with data pipelines, streaming ingestion, and analytical stores (e.g., SQL, columnar/OLAP) for high-volume telemetry
  • Experience with LLM gateways, model routing, vendor abstraction, or cost attribution

What you get

  • 401(k) plan with employer matching
  • 16 weeks of paid parental leave
  • wellness benefits
  • commuter benefits match
  • paid time off
  • paid sick leave

Worth weighing

  • No specific salary listed, but pay range is based on various factors including location and experience
  • The role involves working with rapidly evolving technologies and methodologies, which may require continuous learning and adaptation
  • The job description emphasizes a high-leverage team, which may imply a fast-paced and demanding work environment

Summarised from DoorDash USA's posting. Read the full original.

Listed by DoorDash USA on their greenhouse job board, last confirmed open on 2026-10-23. PitchMeAI is not the employer.

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Apply to a Software Engineer, Machine Learning Infrastructure - Generative AI position at DoorDash USA - Jobs near me at San Francisco, CA; Sunnyvale and 2 more locations