Staff Software Engineer, ML Serving Platform
$131k - $192k USD
About the Team
DoorDash is building the world’s most reliable on-demand logistics engine. Behind the scenes, our Machine Learning Platform (MLP) powers critical real-time decision-making for millions of orders each day, supporting business-critical use cases like Ads, Groceries, Logistics, Fraud, and Search.
About the Role
We’re looking for a Staff Software Engineer with deep expertise in ML model serving to drive the next generation of our inference platform. This is a highly technical, hands-on role: you’ll design and build systems that power real-time predictions across millions of requests per second, tackling challenges in reliability, efficiency, and cost-aware scaling. Success in this role requires both technical mastery and the ability to lead through collaboration. You’ll collaborate with core infrastructure teams (compute, storage, networking, dev platform) and with applied ML teams across Ads, Fraud, Logistics, Search, and more who depend on our platform to bring their models to production. You’ll also tap into the best of open-source frameworks and vendor solutions - contributing back where it makes sense - to accelerate innovation. As Staff Software Engineer, you’ll pair deep technical execution with influence on the roadmap, ensuring our serving systems scale reliably as model architectures and business needs evolve.
In this role, you will:
- Scale richer models at low latency - Design serving systems that handle large, complex models while balancing cost, throughput, and strict latency SLOs.
- Bring modern inference optimizations into production - Operationalize advances from the ML serving ecosystem (e.g. efficient caching, attention optimizations, batching, quantization) to deliver better user experience, latency, and cost efficiency across our fleet.
- Enable platform-wide impact - Build abstractions and primitives that let serving improvements apply broadly across many workloads, rather than point solutions for individual models.
- Leverage and contribute to OSS - Apply the best of the open-source serving ecosystem and vendor solutions, and contribute improvements back where it helps the community.
- Drive cost & reliability - Design autoscaling and scheduling across heterogeneous hardware (GPU/TPU/CPU), with strong isolation, observability, and tail-latency control.
- Collaborate broadly - Partner with ML engineers, infra teams, external vendors, and open-source communities to ensure our serving stack evolves with the needs of the business.
- Raise the engineering bar - Establish metrics & processes that improve developer velocity, system reliability, and long-term maintainability.
We’re excited about you because…
- Have 8+ years of engineering experience, including building or operating large-scale, high-QPS ML serving systems.
- Bring deep familiarity with ML inference and serving ecosystems.
- Know how to leverage and extend open-source frameworks and evaluate vendor solutions pragmatically.
- Balance hands-on execution with long-term platform thinking, making sound trade-offs.
- Care deeply about reliability, performance, observability, and security in production systems.
- Lead by example - collaborating effectively, mentoring peers, and setting a high bar for craftsmanship.
Nice To Haves
- GPU serving expertise - Experience with frameworks like NVIDIA Triton, TensorRT-LLM, ONNX Runtime, or vLLM, including hands-on use of KV caching, batching, and memory-efficient inference.
- Familiarity with deep learning frameworks (PyTorch, TensorFlow) and large language models (LLMs) such as GPT-OSS or BERT.
- Hands-on experience with Kubernetes/EKS, microservice architectures, and large-scale orchestration for inference workloads.
- Cloud experience (AWS, GCP, Azure) with a focus on scaling strategies, observability, and cost optimization.
- Prior contributions to OSS serving ecosystems (e.g., vLLM, Triton plugins, KServe) or active participation in developer communities.
Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only
We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.
The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey
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. Ranges are market-dependent and may be modified in the future.
In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.
DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). 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:
- For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year.
- For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week).
The national base pay ranges for this position within the United States, including Illinois and Colorado.
I4
$130,600—$192,000 USD
I5
$159,800—$235,000 USD
I6
$193,800—$285,000 USD
About DoorDash
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. We are a technology and logistics company that started by enabling door-to-door delivery, and we are looking for team members who can help us go from a company that is known as the place you order food to a company that people turn to for any and all goods.
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. We're committed to supporting employees’ happiness, healthiness, and overall well-being by providing comprehensive benefits and perks including premium healthcare, wellness expense reimbursement, paid parental leave and more.
Our Commitment to Diversity and Inclusion
We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.
Statement of Non-Discrimination: In keeping with our beliefs and goals, no employee or applicant will face discrimination or harassment based on: race, color, ancestry, national origin, religion, age, gender, marital/domestic partner status, sexual orientation, gender identity or expression, disability status, or veteran status. Above and beyond discrimination and harassment based on “protected categories,” we also strive to prevent other subtler forms of inappropriate behavior (i.e., stereotyping) from ever gaining a foothold in our office. Whether blatant or hidden, barriers to success have no place at DoorDash. 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. Thank you to the Level Playing Field Institute for this statement of non-discrimination.
Pursuant to the San Francisco Fair Chance Ordinance, Los Angeles Fair Chance Initiative for Hiring Ordinance, and any other state or local hiring regulations, we will consider for employment any qualified applicant, including those with arrest and conviction records, in a manner consistent with the applicable regulation.
If you need any accommodations, please inform your recruiting contact upon initial connection.