Staff Software Engineer, ML Serving Platform

About the Team

DoorDash is building the world’s most reliable on-demand logistics engine. Our Machine Learning Platform (MLP) powers real-time decision-making for millions of orders each day, supporting Ads, Groceries, Logistics, Fraud, and Search.

About the Role

We’re seeking 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: design and build systems that power real-time predictions across millions of requests per second, addressing reliability, efficiency, and cost-aware scaling. You will collaborate with core infrastructure teams and applied ML teams across Ads, Fraud, Logistics, and Search who depend on our platform to productionize models. You’ll leverage open-source frameworks and vendor solutions and contribute back where it makes sense. As Staff Software Engineer, you will 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 improve user experience, latency, and cost efficiency across our fleet.
• Enable platform-wide impact - Build abstractions and primitives that let serving improvements apply broadly across workloads, not just point solutions for individual models.
• Leverage and contribute to OSS - Utilize open-source serving ecosystems and vendor solutions and contribute improvements 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 evolve our serving stack with business needs.
• Raise the engineering bar - Establish metrics and 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 with frameworks like NVIDIA Triton, TensorRT-LLM, ONNX Runtime, or vLLM, including KV caching, batching, and memory-efficient inference.
• Familiarity with 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, observability, and cost optimization.
• Prior contributions to OSS serving ecosystems or active participation in developer communities.

Compensation

The successful candidate’s starting pay falls within the listed range and is determined by factors including skills, experience, location, and market conditions. Base salary is localized by work location. Ranges are market-dependent and may change. In addition to base salary, compensation includes opportunities for equity grants. Information provided by the recruiter can be shared as needed.

DoorDash offers a comprehensive benefits package, including 401(k) with employer matching, paid parental leave, wellness benefits, commuter benefits match, paid time off and sick leave, medical/dental/vision benefits, paid holidays, disability and life insurance, family-forming assistance, and a mental health program. For more details, see the careers page.

Paid time off details: salaried roles — flexible PTO plus paid sick time; hourly roles — vacation and sick time accrual as described in company policy.

About DoorDash

DoorDash empowers local economies by moving quickly, learning, and iterating to make impactful decisions for Dashers, merchant partners, and consumers. We are a technology and logistics company evolving from food delivery to a broader on-demand platform.

Our Commitment to Diversity and Inclusion

We are committed to building an inclusive community with diverse teams from all backgrounds, experiences, and perspectives. We believe true innovation happens when everyone has a seat at the table and access to tools and opportunities to excel.

Statement of Non-Discrimination: We do not discriminate or harass based on protected categories and strive to prevent stereotype-driven barriers to success. We encourage applicants from diverse backgrounds to apply. If you need accommodations, please inform your recruiting contact.