Engineering Manager, Machine Learning Platform
San Francisco, CA; Seattle, WA; Sunnyvale, CA
Full Time Mid-level / Intermediate USD 203K - 299K
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DoorDash
When you join our team, you join our dream: to grow and empower local economies. We’re focused on improvement—from moving faster to leveling up the quality of our product—and our work is never complete. If you’re looking to define your career...
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 TeamDoorDash 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 RoleWe 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.
- 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.
- 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.
- We are leaders - Leadership is not limited to our management team. It’s something everyone at DoorDash embraces and embodies.
- We are doers - We believe the only way to predict the future is to build it. Creating solutions that will lead our company and our industry is what we do -- on every project, every day.
- We are learning - We’re not afraid to dig in and uncover the truth, even if it’s scary or inconvenient. Everyone here is continually learning on the job, no matter if we’ve been in a role for one year or one minute.
- We are customer obsessed - Our mission is to grow and empower local economies. We are committed to our customers, merchants, and dashers and believe in connecting people with possibility.
- We are all DoorDash - The magic of DoorDash is our people, together making our inspiring goals attainable and driving us to greater heights.
- We offer great compensation packages and comprehensive health benefits.
Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only
We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.
The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey
CompensationThe successful candidate's starting pay will fall within the pay range listed below and is determined based on job-related factors including, but not limited to, skills, experience, qualifications, work location, and market conditions. Base salary is localized according to an employee’s work location. Ranges are market-dependent and may be modified in the future.
In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.
DoorDash cares about you and your overall well-being. That’s why we offer a comprehensive benefits package for all regular employees that includes a 401(k) plan with an employer match, paid time off, paid parental leave, wellness benefits, and several paid holidays. Paid sick leave in compliance with applicable laws (i.e. Colorado Healthy Families and Workplaces Act).
Additionally, for full-time employees, DoorDash offers medical, dental, and vision benefits, disability and basic life insurance, family-forming assistance, a commuter benefit match, and a mental health program, among others.
To learn more about our benefits, visit our careers page here.
The base pay for this position ranges from our lowest geographical market up to our highest geographical market within the United States.$203,500—$299,300 USDAbout DoorDashAt DoorDash, our mission to empower local economies shapes how our team members move quickly, learn, and reiterate in order to make impactful decisions that display empathy for our range of users—from Dashers to merchant partners to consumers. We are a technology and logistics company that started with door-to-door delivery, and we are looking for team members who can help us go from a company that is known for delivering food to a company that people turn to for any and all goods.
DoorDash is growing rapidly and changing constantly, which gives our team members the opportunity to share their unique perspectives, solve new challenges, and own their careers. We're committed to supporting employees’ happiness, healthiness, and overall well-being by providing comprehensive benefits and perks including premium healthcare, wellness expense reimbursement, paid parental leave and more.
We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel.
Statement of Non-Discrimination: In keeping with our beliefs and goals, no employee or applicant will face discrimination or harassment based on: race, color, ancestry, national origin, religion, age, gender, marital/domestic partner status, sexual orientation, gender identity or expression, disability status, or veteran status. Above and beyond discrimination and harassment based on “protected categories,” we also strive to prevent other subtler forms of inappropriate behavior (i.e., stereotyping) from ever gaining a foothold in our office. Whether blatant or hidden, barriers to success have no place at DoorDash. We value a diverse workforce – people who identify as women, non-binary or gender non-conforming, LGBTQIA+, American Indian or Native Alaskan, Black or African American, Hispanic or Latinx, Native Hawaiian or Other Pacific Islander, differently-abled, caretakers and parents, and veterans are strongly encouraged to apply. Thank you to the Level Playing Field Institute for this statement of non-discrimination.
Pursuant to the San Francisco Fair Chance Ordinance, Los Angeles Fair Chance Initiative for Hiring Ordinance, and any other state or local hiring regulations, we will consider for employment any qualified applicant, including those with arrest and conviction records, in a manner consistent with the applicable regulation.
If you need any accommodations, please inform your recruiting contact upon initial connection.
Tags: AWS Azure CX Data pipelines Distributed Systems Engineering Excel Feature engineering GCP Machine Learning ML infrastructure ML models MLOps Model inference Model training Pipelines
Perks/benefits: 401(k) matching Career development Equity / stock options Health care Insurance Medical leave Parental leave Salary bonus Wellness
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