About the Team DoorDash is looking for an Engineering Manager with an ML background to lead the Personalization engineering team. This team is responsible for building ML ranking and recommendation systems to maximize the value for Consumers, Merchants and DoorDash.
Our Personalization team is a part of our Core Consumer org which owns the top of the conversion funnel from the initial landing page all the way to checkout across iOS, Android, and Web platforms. Personalization is at the center of the team's mission. As DoorDash expands into new verticals like Grocery, the challenge of helping consumers easily find what they want grows exponentially, so the opportunity is massive!
About the Role You will lead a team of world-class ML engineers redefining the personalization experience for DoorDash through cutting edge technologies. You will also be the key player in defining DoorDash's personalization strategy and technology roadmap.
You're excited about this opportunity because you will… Lead and grow a team of exceptional machine learning engineers delivering on end-to-end personalization experience with state-of-the-art ML approaches. Leverage cutting edge LLM and Deep Learning (GNN, MTL, Transformers) to augment DoorDash's personalization stack. Work with Product, Design, and Business stakeholders directly across DoorDash to define the roadmap and vision for the team and deliver immense impact. Encourage innovation, implementation of cutting-edge technologies, outside-of-the-box thinking, and teamwork. Build an outstanding team by coaching and empowering engineers through delegation, and applying your technical expertise to hold your team to the highest engineering standards. Scale the team by developing internal talent and attracting top external talent. We're excited about you because you have… B.S., M.S., or PhD. in Computer Science or equivalent. 7+ years of industry experience. Minimum of 2 years of leadership experience. Broad knowledge of machine learning with strong ML modeling foundation. Extensive experience in building user-facing products and working directly with product managers. Strong communication skills and the ability to partner with teams spanning many disciplines. Ability to guide and grow an excellent engineering team in a rapidly changing business environment. Experience in leading successful application of machine learning to ranking and recommendation real-world problems is preferred.
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