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About the Role

As a Machine Learning Engineer on the Drive team, you'll own machine learning systems end-to-end—from feature engineering and model development to experimentation, deployment, monitoring, and continuous iteration. Your work will span several high-impact problem areas including building next-generation ML models for delivery and pickup ETAs, merchant prep-time estimation, and order release prediction. You will also develop deep learning models, apply reinforcement learning and optimization techniques, and build AI-native product experiences using LLMs and VLMs. You will design and run rigorous online experiments, production monitoring, and model iteration, and partner closely with cross-functional teams to bring new ML capabilities into production at scale.

Responsibilities

Build next-generation machine learning models for delivery ETA, pickup ETA, merchant prep-time estimation, and order release prediction that improve reliability for merchants and consumers.
Develop deep learning models that leverage large-scale spatiotemporal, marketplace, and behavioral signals to improve prediction accuracy.
Apply reinforcement learning and optimization techniques to improve logistics decision-making, assignment strategies, and marketplace efficiency.
Build AI-native product experiences using large language models (LLMs) and vision-language models (VLMs).
Design and run rigorous online experiments, production monitoring, and model iteration to continuously improve performance.
Partner closely with software engineers, product managers, data scientists, and platform teams to bring new machine learning capabilities into production at scale.

Requirements

5+ years of industry experience building and shipping production machine learning systems with measurable business impact.
Strong experience developing production machine learning models using modern deep learning frameworks such as PyTorch.
Experience with distributed data processing technologies such as Spark and Airflow.
Experience building, deploying, monitoring, and maintaining production ML systems end-to-end.
Strong software engineering skills in Python.
Experience with modern ML infrastructure and tooling.
Deep expertise in at least one of the following areas: Deep Learning, Reinforcement Learning, Optimization / Operations Research, Large Language Models (LLMs) or Vision-Language Models (VLMs).
Experience applying machine learning to estimation, ranking, prediction, optimization, or decision-making problems at production scale.
Hands-on experience with LLMs or VLMs is a strong plus.
Experience in logistics, marketplaces, or delivery platforms is helpful but not required.
Proficiency using AI-assisted development tools (e.g. Claude Code, Codex, Cursor) throughout the software development lifecycle.

Skills

PyTorch
Spark
Airflow
Python
Deep Learning
Reinforcement Learning
Optimization
Operations Research
Large Language Models (LLMs)
Vision-Language Models (VLMs)
AI-assisted development tools

Location

San Francisco, CA
Sunnyvale, CA
Seattle, WA

Work Type

Full-time

Experience Level

5+ years of industry experience

Education Level

Bachelor's
Master's
PhD

Salary/Compensations

$137,100—$201,600 USD
$167,800—$246,800 USD
$203,500—$299,300 USD

Benefits

401(k) plan with employer matching
16 weeks of paid parental leave
Wellness benefits
Commuter benefits match
Paid time off
Paid sick leave
Medical benefits
Dental benefits
Vision benefits
11 paid holidays
Disability and basic life insurance
Family-forming assistance
Mental health program

About the Company

At 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 by enabling door-to-door delivery, and we are looking for team members who can help us go from a company that is known as the place you order 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.

Equal Opportunity

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.