DoorDash

DoorDash

Software Engineer, ML Infrastructure (MDX)

US · Mid

Sponsorship not specified$131k-$192kDetected 5 days ago
PythonDistributed SystemsAWSGCPCloud PlatformsKubernetesMachine LearningAirflowData EngineeringLLMsAgentic AIMLOpsAI OrchestrationA/B TestingLogisticsResearchLeadership

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odds of building a lasting career here

64Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

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Employer immigration record

from this employer's Department of Labor filings

Green-card filing pattern in this occupation

Context, not a finding about this posting: of this employer's 22 green-card filings in this occupation, 100% were for a worker who already held the job.

Green-card follow-through: 53%

Of 34 labor certifications old enough to have been used, 16 expired without the employer filing the next step. Median time from filing to decision: 481 days.100% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.

Files H-1B transfers

125 transfer filings in the last year, covering 125 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • We work across the full ML lifecycle: feature engineering, training, evaluation, deployment, serving, and monitoring.
  • Our mission is to increase the velocity and reliability of ML-driven business impact across the company.
  • A central pillar of that work is agentic infrastructure.

Responsibilities

  • You'll design and build the systems that let agents accelerate how ML engineers across DoorDash, Wolt, and Deliveroo develop, ship, and operate models.
  • That includes auto research systems that explore and iterate on modeling ideas, and agentic developer support that helps ML engineers move through training, evaluation, deployment, and debugging faster.
  • You'll own well-scoped components end to end, from design through production, working across agent orchestration, tooling and integrations with our ML platform, evaluation of agent behavior, and observability.
  • Build agentic systems that increase the velocity of ML development across DoorDash, Wolt, and Deliveroo, helping ML engineers get from idea to production model faster.
  • Design and implement infrastructure that lets agents propose, run, and evaluate modeling experiments.
  • Build agentic developer support for the ML lifecycle, such as agents that help engineers set up training jobs, debug failing pipelines, review model deployments, and navigate our platform.
  • Develop evaluation and observability for agent behavior, so we can measure whether agents are actually helping, catch regressions early, and build the trust needed to give them more autonomy.
  • Grow quickly in a fast-moving area, with the chance to shape how agents are used to build and operate ML systems at a company of this scale.
  • At DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users-from Dashers to merchant partners to consumers.
  • DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers.

Requirements

  • Ability to take ambiguous, well-scoped problems from idea to production, and to learn quickly in a fast-moving technical area
  • Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) across the software development lifecycle, including designing, generating code, testing, monitoring, and releasing software
  • Experience with agent evaluation, LLM observability, tracing, or building eval harnesses

Compensation

  • The successful candidate's starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions.
  • Base salary is localized according to an employee's work location.
  • In addition to base salary, the compensation for this role includes opportunities for equity grants.
  • flexible paid time off/vacation, plus 80 hours of paid sick time per year.
  • For hourly roles:
  • The national base pay range for this position within the United States, including Illinois and Colorado.

Benefits

  • DoorDash's MDX team sits within Machine Learning Platform and builds the shared foundation that ML engineers across DoorDash, Wolt, and Deliveroo rely on to build and run ML-powered products.
  • DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.
  • To learn more about our benefits, visit our careers page here.
  • See below for paid time off details:

Company info

  • We work across the full ML lifecycle:
  • feature engineering, training, evaluation, deployment, serving, and monitoring.
  • We are building systems that let agents accelerate and operate the ML workflow itself, including auto research, where agents explore and iterate on modeling ideas, and self-healing systems that detect, diagnose, and remediate failures in ML pipelines and production models with minimal human intervention.

Equal opportunity

  • Our Commitment to Diversity and Inclusion
  • 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.
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This listing is sourced directly from DoorDash's careers page and normalized into a canonical job model.