Engineering Manager, Personalization

DoorDash USA•Sunnyvale, CA

12h•$193,800 - $285,000

About The Position

DoorDash is seeking an Engineering Manager with a machine learning background to lead the Personalization engineering team within the Core Consumer organization. The team builds machine-learning ranking and recommendation systems designed to maximize value for consumers, merchants, and DoorDash. It owns personalization across the consumer conversion funnel, from the initial landing page through checkout, as DoorDash expands into experiences and verticals such as grocery, reservations, and going out. The manager will lead a team of machine learning engineers and help define DoorDash’s personalization strategy, technical roadmap, and vision. The team’s planned work includes developing an intent agent that predicts what consumers are looking for when they open the app; applying LLMs and deep-learning approaches to improve semantic understanding of ranked entities; blending content across verticals and business lines; and implementing real-time ranking that responds to consumer signals. The role partners closely with Product, Design, and Business stakeholders, and is responsible for coaching and empowering engineers, maintaining high engineering standards, and growing the team through internal development and external recruiting. The position offers a U.S. national base salary range of $193,800–$285,000, localized by work location, and opportunities for equity grants. DoorDash’s benefits package for regular employees includes a 401(k) with employer matching, paid parental leave, wellness and commuter benefits, paid time off and sick leave, medical, dental, and vision benefits, paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program. Salaried roles offer flexible paid time off and 80 hours of paid sick time per year.

Requirements

B.S., M.S., Ph.D. in Computer Science, or equivalent.
At least 7 years of industry experience.
At least 2 years of leadership experience.
Broad knowledge of machine learning and a strong machine-learning modeling foundation.
Extensive experience building user-facing products and working directly with product managers.
Strong communication skills and ability to partner across disciplines.
Ability to guide and grow an engineering team in a rapidly changing business environment.

Nice To Haves

Experience leading successful applications 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 machine-learning systems.

Responsibilities

Lead a team of machine learning engineers building end-to-end personalization experiences.
Define the personalization strategy, technology roadmap, and team vision.
Build an intent agent that predicts consumer intent when the app opens and shapes the experience around it.
Use LLMs and deep-learning approaches to augment the personalization stack and improve semantic understanding of ranked entities.
Extend systems that blend content from different verticals and business lines while balancing value for consumers, merchants, and DoorDash.
Advance personalization toward real-time ranking that responds to consumer signals as they happen.
Partner with Product, Design, and Business stakeholders to define the roadmap and deliver impact.
Encourage innovation, adoption of advanced technologies, creative thinking, and teamwork.
Coach and empower engineers through delegation and uphold high engineering standards.
Grow the team by developing internal talent and attracting external talent.