Software Engineer, Machine Learning Infrastructure

At DoorDash, we're building the world's most reliable on-demand logistics engine for delivery. We're seeking talented engineers to create and maintain a 24x7, no downtime, global infrastructure system that powers DoorDash's three-sided marketplace of consumers, merchants, and dashers.

As a Software Engineer in Machine Learning Infrastructure, you'll join a small team to build systems that empower efficient machine learning at scale. You'll work closely with Data Scientists and Product Engineers to evolve the ML platform, build high-performance and flexible pipelines, and design infrastructure solutions to store trillions of feature values and power hundreds of billions of predictions daily.

Key responsibilities include:

• Building a world-class ML platform for seamless model development, training, and deployment
• Designing and driving directions for the centralized machine learning platform
• Improving the reliability, scalability, and observability of training and inference infrastructure
• Working on infrastructure designs to handle massive amounts of data and predictions

We're looking for candidates with:

• B.S., M.S., or PhD. in Computer Science or equivalent
• Strong knowledge of CS fundamentals and OOP languages
• 4+ years of industry experience in software engineering
• Experience building machine learning systems in production
• Systems engineering experience, especially in cloud computing environments

This is a hybrid opportunity available in San Francisco, Sunnyvale, or Seattle.

DoorDash offers comprehensive benefits including healthcare, 401(k) with employer match, paid time off, parental leave, and equity grants. We're committed to diversity, inclusion, and empowering our employees' well-being and career growth.

Join us in shaping the future of on-demand delivery and logistics!