Software Engineer, Machine Learning Infrastructure - Gen AI

DoorDash, Inc

Quick summary

Work type
On-site
Location
San Francisco, CA
Salary
$137,100–$201,600 / yr
Posted
2 days ago

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $202k
This role $169k
$125k most similar roles pay here $254k

This role pays less than 72% of similar roles. Most pay $167,537–$235,750 — the shaded band above. At the midpoint, this role pays about $169k versus about $202k for comparable roles.

Based on 240 similar postings.

Employer

About DoorDash, Inc

DoorDash, Inc. is an American company operating online food ordering and food delivery. It trades under the symbol DASH. With a 56% market share, DoorDash is the largest food delivery platform in the United States.

DoorDash, Inc currently has 244 open roles on FindRole.

Listed pay typically runs $133,300–$196,000 across 166 roles with salary data.

Most-posted roles

View all roles at DoorDash, Inc

At a glance

TL;DR · Software Engineer, Machine Learning Infrastructure - Gen AI

As a Software Engineer at DoorDash’s GenAI Platform team, you will join a small, high-impact group building the infrastructure that enables DoorDash teams to transition generative AI ideas from prototypes to production. Your daily work will involve designing and implementing scalable systems for AI agents, model serving, batch inference, evaluation workflows, and observability, ensuring reliability and cost efficiency. You’ll use Python and distributed systems extensively while working on core platform components like the LLM Gateway and Agent Gateway. Ideal candidates have 4+ years of experience in backend engineering with a focus on production services, APIs, data pipelines, and ML infrastructure at scale. Familiarity with machine learning workflows and cloud infrastructure is essential, as you will collaborate closely with cross-functional teams to drive innovation in AI-powered products and automation across DoorDash, Wolt, and Deliveroo.

What you'll do

  • Build infrastructure to move GenAI ideas from prototype to production.
  • Design scalable systems for AI agents, tool orchestration, and evaluation workflows.
  • Help product teams choose the right model and vendor strategy with reliability built in.
  • Support rapid experimentation while meeting production standards for latency and scale.
  • Partner with ML engineers and platform teams to turn emerging GenAI capabilities into primitives.

What we're looking for

  • 4+ 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 with focus on observability, debugging, reliability, and performance optimization
  • Familiarity with machine learning workflows including inference, evaluation, feature/data pipelines, model serving, and experimentation
  • Ability to work across ambiguous, fast-moving technical areas and turn customer use cases into reusable platform capabilities

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