DoorDash

DoorDash

Software Engineer, ML Serving Platform

US · Mid · Contract

Sponsorship not specified$131k-$192kDetected 11 days ago
JavaGoC++KotlinDistributed SystemsKubernetesMachine LearningLogistics

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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

  • Our customers are modelers and engineering teams across our internal business verticals.
  • We work at the intersection of a rapidly evolving open source ecosystem and demanding production workloads.
  • You'll tackle challenging infrastructure problems involving latency, reliability, resource efficiency, and scale, and make those capabilities accessible through self-serve tools and workflows.

Responsibilities

  • You'll help build the next generation of our ML serving platform, connecting request routing and online feature retrieval with model inference on CPU and GPU infrastructure.
  • Working alongside experienced platform engineers, you'll own defined projects from technical design and implementation through testing, rollout, and production support.
  • Help evolve our disaggregated serving architecture. Build modular components that allow routing, feature retrieval, and model execution to evolve and scale independently as workloads and modeling requirements change.
  • Make adoption and rollout easier. Build integrations, validation, and migration tooling that help teams adopt new serving capabilities and our unified global platform with confidence.
  • Own performance and reliability in production. Use benchmarking, profiling, metrics, and tracing to identify bottlenecks; participate in on-call and improve automation and runbooks to make the platform easier to operate.
  • 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

  • You have strong computer science fundamentals and proficiency in a backend or systems programming language such as Java, Kotlin, Go, C++, or Python.
  • You have experience debugging production systems and using operational data to improve reliability, performance, or cost.
  • You hold a degree in Computer Science or a related field, or have equivalent practical experience.

Nice to have

  • Experience with ML inference infrastructure, online feature retrieval, or other latency-sensitive distributed services.
  • Experience operating containerized workloads on Kubernetes, including deployment, resource management, or autoscaling.
  • Experience integrating open source infrastructure or models and validating their behavior under production workloads.
  • Familiarity with CPU/GPU performance profiling, inference runtimes, or model deployment workflows.
  • Applications for this position are accepted on an ongoing basis
  • Ranges are market-dependent and may be modified in the future.
  • Talk to your recruiter for more information.
  • DoorDash cares about you and your overall well-being.

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

  • We build self-serve infrastructure that empowers them to bring new models into production, adopt open source software and models, and expand what they can accomplish with machine learning at scale.
  • 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

  • DoorDash's ML Serving Platform delivers tens of millions of predictions per second, powering search, recommendations, advertising, delivery estimates, and logistics across DoorDash, Wolt, and Deliveroo.
  • With active customer demand and growing modeling ambitions, we're advancing the infrastructure behind today's predictions while building the capabilities that enable the next generation of ML innovation.
  • You care about the engineers using your platform and collaborate effectively with customers and partners to make complex infrastructure easier to adopt.

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.