
Software Engineer, Infrastructure - Autonomy & Robotics
DoorDash · San Francisco, CA
- On site
- Full-time
- $192,000 / year
- San Francisco, CA
Job highlights
- Develop and improve autonomy and robotics infrastructure.
- Design large-scale simulation and data processing systems.
- Build infrastructure for autonomous vehicle development.
- Process petabyte-scale datasets and GPU-accelerated computing.
- Collaborate with core autonomy and engineering teams.
About the role
About The Team
DoorDash Labs, established in 2018, serves as the innovation hub for DoorDash, focusing on developing automation and robotics solutions to enhance last-mile logistics. The team's mission is to create technologies that support and augment human networks, aiming to improve efficiency for Dashers, merchants, and consumers alike. We’re ruthlessly focused on business impact. We are a highly senior team composed of former pioneers from a variety of different robotics industries. As of 2025, DoorDash has completed 10B lifetime deliveries. We’re focused on how to do the next 10B even better.
About The Role
We’re hiring an Infrastructure Software Engineer. In this role, you’ll work with multiple stakeholders including Product, Engineering, and Operations to develop and improve our infrastructure. The Infrastructure team designs, builds, and operates the infrastructure that enables large scale simulation testing, continuous integration, and machine learning.
You’re Excited About The Role Because You Will…
- Have significant scope and decision-making responsibility.
- Design and implement infrastructure to enable autonomous vehicle development, including:
- Large-scale distributed simulation execution
- Ingest, processing, and organization of petabyte-scale datasets
- GPU-accelerated distributed computing for data preparation and training
- Design and implement robot data and metrics pipelines.
- Collaborate with core autonomy teams: motion planning, perception, and simulation.
We’re Excited About You Because You Have…
- A B.S., M.S., or PhD. in Computer Science, Robotics or related technical field.
- In-depth knowledge of data structures and algorithms.
- Strong Python programming experience.
- Experience with operationalizing large-scale systems.
- Experience with at least one distributed data processing framework (Ray, Spark, Flink, etc).
- Passionate about software quality and reliability.
Nice to have:
- C++
- SQL
- Kubernetes
- Docker
- Terraform
- Experience with GPU-accelerated systems
- Robotics domain experience/knowledge
Must be comfortable regularly exercising discretion and independent judgment in performing job duties, including evaluating options, making informed decisions, and determining appropriate courses of action within the scope of assigned responsibilities.
Key skills/competency
- Infrastructure Software Engineering
- Robotics
- Autonomous Vehicle Development
- Distributed Systems
- Large-scale Data Processing
- Python
- Machine Learning Infrastructure
- Simulation Testing
- Data Pipelines
- System Operations
Skills & topics
- Software Engineer
- Infrastructure
- Robotics
- Autonomy
- Python
- Distributed Systems
- Data Engineering
- Machine Learning
- Simulation
- Cloud Computing
How to get hired
- Tailor your resume: Highlight experience with large-scale systems, Python, and distributed data processing frameworks relevant to infrastructure engineering.
- Showcase your projects: Emphasize any personal or professional projects demonstrating your skills in robotics, simulation, or data pipelines.
- Prepare for technical questions: Brush up on data structures, algorithms, and system design principles, especially those related to distributed computing and ML infrastructure.
- Understand DoorDash: Research DoorDash's mission, values, and the specific goals of their innovation hub to align your answers with their strategic objectives.
- Ask insightful questions: Prepare questions about the team's challenges, future projects, and the impact of infrastructure on autonomous systems.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the key technical skills required for the Software Engineer, Infrastructure role at DoorDash Labs?
- The Software Engineer, Infrastructure role at DoorDash Labs requires a strong foundation in Python programming, data structures, and algorithms. Experience with operationalizing large-scale systems and at least one distributed data processing framework (like Ray, Spark, or Flink) is crucial. Familiarity with C++, SQL, Kubernetes, Docker, Terraform, and GPU-accelerated systems are considered beneficial.
- What kind of projects will I be working on as an Infrastructure Software Engineer at DoorDash?
- As an Infrastructure Software Engineer at DoorDash Labs, you will design and implement infrastructure for autonomous vehicle development. This includes large-scale distributed simulation execution, processing petabyte-scale datasets, and GPU-accelerated distributed computing for data preparation and training. You'll also develop robot data and metrics pipelines.
- What is DoorDash Labs and what is its mission?
- DoorDash Labs is the innovation hub for DoorDash, established in 2018. Its mission is to develop automation and robotics solutions to enhance last-mile logistics, creating technologies that support and augment human networks to improve efficiency for Dashers, merchants, and consumers.
- What educational background is preferred for the Infrastructure Software Engineer position?
- DoorDash prefers candidates with a B.S., M.S., or PhD. in Computer Science, Robotics, or a related technical field for the Infrastructure Software Engineer role. This ensures a strong theoretical and practical understanding of the required technical domains.
- How does DoorDash approach compensation and benefits for its employees?
- DoorDash offers competitive compensation including base salary, equity grants, and a comprehensive benefits package. Benefits include 401(k) with employer matching, paid parental leave, wellness benefits, medical, dental, and vision insurance, and paid time off. Salary ranges are provided and are dependent on factors like experience and location.
- Is this role remote, hybrid, or on-site, and are there specific location requirements?
- The job description mentions specific notices for jobs located in NYC or remote jobs associated with an office in NYC, suggesting potential for remote or hybrid arrangements, especially in certain locations. However, the core job description does not explicitly state the work arrangement or definitive location, beyond mentioning national base pay ranges within the United States. Candidates should clarify this with the recruiter.