Engineering Manager, Personalization

About This Role

This engineering manager role leads the Personalization team, which is responsible for building ML ranking and recommendation systems to maximize value for consumers, merchants, and DoorDash. The team is part of the Core Consumer organization, owning the conversion funnel from the initial landing page to checkout across platforms. The role suits an engineering manager with an ML background who will redefine the personalization experience through cutting-edge technologies.

Responsibilities

• Build an intent agent that makes granular predictions of what each consumer is here for the moment they open the app, and shapes the experience around it
• Leverage cutting-edge LLM and Deep Learning (GNN, MTL, Transformers) to augment DoorDash’s personalization stack, starting with semantic understanding of every entity ranked, so models understand what consumers want and what is offered, not just what they clicked before
• Extend the blender to blend content from different verticals and business lines, like reservations, going out, and ads, balancing value for consumers, merchants, and DoorDash
• Take personalization to real-time ranking that reacts to consumer signals as they happen
• Lead and grow a team of exceptional machine learning engineers delivering on end-to-end personalization experience with state-of-the-art ML approaches
• 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 technical expertise to hold the team to the highest engineering standards
• Scale the team by developing internal talent and attracting top external talent

Requirements

• 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 product 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

Nice to have:

• Experience leading the successful application of machine learning to real-world ranking and recommendation problems
• Experience with LLM-powered agents, semantic representations of users and content, multi-objective blending, or real-time ML systems

Benefits