Staff Engineer • Senior

Who you are

You have extensive experience in software engineering, particularly in building and scaling machine learning systems — your expertise in ML model serving allows you to tackle complex challenges in reliability and efficiency. You are proficient in Python and have a strong understanding of cloud platforms like AWS, which you leverage to optimize model performance and cost. Your background includes hands-on experience with containerization technologies such as Docker and orchestration tools like Kubernetes, enabling you to deploy scalable solutions effectively.

You possess a collaborative mindset, working closely with infrastructure teams and applied ML teams across various domains including Ads, Fraud, and Logistics — your ability to communicate technical concepts clearly fosters strong partnerships and drives project success. You are comfortable contributing to open-source frameworks and vendor solutions, enhancing innovation within your team and the broader community.

Your leadership skills shine through as you influence the roadmap for ML serving systems, ensuring they evolve alongside changing model architectures and business needs. You thrive in environments that require both technical mastery and strategic thinking, allowing you to make impactful decisions that drive the organization forward.

Desirable

Experience with real-time data processing and high-throughput systems is a plus, as is familiarity with machine learning frameworks such as TensorFlow or PyTorch. You are also encouraged to bring any experience with performance optimization techniques and cost-aware scaling strategies to the table.

What you'll do

In this role, you will design and build the next generation of DoorDash's ML inference platform, focusing on systems that can handle millions of requests per second with low latency. You will be responsible for scaling complex models while balancing throughput and strict latency SLOs, ensuring that the platform remains reliable and efficient.

You will operationalize modern inference optimizations, bringing them into production to enhance the performance of machine learning models. Collaborating with core infrastructure teams, you will address challenges related to compute, storage, and networking, ensuring that the ML platform integrates seamlessly with existing systems.

Your role will involve mentoring junior engineers and sharing your knowledge of best practices in ML model serving and system design. You will also participate in code reviews and contribute to the development of technical documentation, fostering a culture of learning and continuous improvement within the team.

What we offer

At DoorDash, you will be part of a mission-driven team that is transforming the logistics industry through innovative technology. We offer competitive compensation packages, including salary and benefits that reflect your skills and experience. You will have the opportunity to work in a collaborative environment that values diversity and encourages professional growth.

Join us in building the world’s most reliable on-demand logistics engine, where your contributions will directly impact millions of customers and businesses. We encourage you to apply even if your experience doesn't match every requirement — your unique perspective could be the key to our success.