DoorDash
Staff Software Engineer, ML Serving Platform
DoorDash, San Francisco, California, United States, 94199
Staff Software Engineer, ML Serving Platform
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Staff Software Engineer, ML Serving Platform
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DoorDash 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. 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 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. 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, 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. Familiarity with deep learning frameworks and large language models. Hands-on experience with Kubernetes, microservice architectures, and large-scale orchestration for inference workloads. Cloud experience with a focus on scaling strategies, observability, and cost optimization. Prior contributions to OSS serving ecosystems or active participation in developer communities. Compensation
The successful candidate's starting pay will fall within the pay range listed below and is determined based on job-related factors. Base salary is localized according to an employee’s work location. Benefits
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. Our Commitment to Diversity and Inclusion
We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. 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.
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Join to apply for the
Staff Software Engineer, ML Serving Platform
role at
DoorDash 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. 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 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. 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, 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. Familiarity with deep learning frameworks and large language models. Hands-on experience with Kubernetes, microservice architectures, and large-scale orchestration for inference workloads. Cloud experience with a focus on scaling strategies, observability, and cost optimization. Prior contributions to OSS serving ecosystems or active participation in developer communities. Compensation
The successful candidate's starting pay will fall within the pay range listed below and is determined based on job-related factors. Base salary is localized according to an employee’s work location. Benefits
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. Our Commitment to Diversity and Inclusion
We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. 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.
#J-18808-Ljbffr