Come help us build the world's most reliable on-demand, logistics engine for delivery! We're bringing on talented engineers to help us create and maintain a 24x7, no downtime, global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers.

About the Team

DoorDash is a machine learning driven organization and relies on machine learning to improve customer experience, power many business and product decisions, and to reduce cost. The Machine Learning Platform owns all the infrastructure necessary to enable DoorDash engineers to quickly and efficiently apply machine learning.  The platform covers the entire ML development lifecycle, which includes featuring engineering, feature store, model store, model training, model inference and ML observability, and more

About the Role

We are seeking an experienced and highly motivated Engineering Manager to lead our Feature Platform team within the Machine Learning Platform (MLP) organization. In this critical role, you will manage the redesign and operations of our Feature Store and broader Feature Platform, which serves as the backbone for machine learning across the company. This platform powers model training and inference at scale, ensuring data consistency, low-latency access, and high availability for real-time and batch features.

As the Engineering Manager for the Feature Platform, you will lead a high-performing team of engineers, driving both the technical vision and execution. You will work closely with ML managers, product teams, and other platform teams to understand business needs, align priorities, and deliver a robust platform that accelerates ML development and improves model performance. This is a high-visibility, high-impact role at the center of the company's ML strategy.

You’re excited about this opportunity because you will…

• Be at the center of the company’s ML strategy with visibility and influence across multiple business and product areas.
• Lead a central, high-impact team that powers machine learning across the company, directly influencing the success of ML models and business outcomes.
• Shape the future of the Feature Platform by defining the technical strategy and driving key architectural decisions.
• Collaborate with top ML and product leaders to deliver innovative solutions that accelerate model development and deployment.
• Solve complex engineering challenges at scale, including low-latency feature serving, data consistency, and real-time feature updates.
• Mentor and grow a team of talented engineers, creating a strong culture of technical excellence and professional development.

We’re excited about you because…

• You possess deep technical expertise in feature stores, data pipelines, and ML infrastructure, with a track record of delivering scalable and reliable solutions.
• You have a strong background in building and managing large-scale ML platforms and understand the complexities of feature engineering and real-time serving.
• You have proven experience leading high-performing engineering teams and fostering a culture of technical excellence and innovation.
• You excel at collaborating with cross-functional teams — including ML scientists, product managers, and data engineers — to align platform capabilities with business needs.
• You are passionate about mentoring and developing engineers, helping them grow their skills and careers.

What You'll Need

• 8+ years of industry experience in software engineering, machine learning, or infrastructure.
• 2+ years of experience in an engineering management role, leading teams focused on building infrastructure or platform solutions.
• Experience building and operating feature stores or ML platforms — you understand the complexities of managing features at scale and enabling seamless access for training and inference.
• Deep interest in machine learning and MLOps, with a strong understanding of how ML models are built, deployed, and maintained.
• Hands-on experience with machine learning infrastructure — you’ve designed and built significant infrastructure components in a cloud environment. Bonus if you've worked on data processing or distributed systems.
• Proficiency in cloud-based environments such as AWS, GCP, or Azure.

Why You’ll Love Working at DoorDash

• We are leaders - Leadership is not