Job description

About the Role DoorDash is building an AI Research org from the ground up, and we're hiring our founding researchers. This is not a role inside an existing team — it's a role that defines what the team becomes. You'll have an outsized influence on the research agenda, hiring, culture, infrastructure choices, and how research connects to the rest of DoorDash. DoorDash sits on a uniquely valuable substrate for AI research: a real-world, multi-sided marketplace operating at massive scale, with millions of consumers, merchants, and Dashers generating data that no academic lab and few companies can access. We want to build a research org that takes that seriously — one that produces work the broader field cares about, and that fundamentally reshapes how local commerce works. You should apply if you want to do ambitious, publishable research in an environment with the data, compute, and operational reach to actually deploy what you build. What You'll Do Set the research agenda for one or more areas of DoorDash AI Research, in close collaboration with the founding team and leadership Lead high-impact research projects end-to-end — from problem framing through publication and, where appropriate, production deployment Help build the team — interview, recruit, and mentor researchers, engineers, and fellows joining the org Shape the org's culture and operating model — how we publish, how we collaborate with product teams, how we balance open research with proprietary work Partner across DoorDash with ML platform, product, and operations teams to identify the highest-leverage research bets and translate findings into real-world impact What You'll Have Access To Novel proprietary data at marketplace scale — logistics traces, merchant operations, consumer behavior, real-time supply and demand signals, and longitudinal data unavailable anywhere else Scalable data collection — ability to design and run structured data collection, leveraging DoorDash’s world-class operational scale, from in-the-wild image and video capture to operational task demonstrations and human-in-the-loop annotation, at a scale and physical-world coverage no other org can match High compute budgets for training and inference, sized to support frontier-scale experimentation including large-model pre-training and post-training, RL training runs, and large-scale evaluation sweeps Full research infrastructure — DoorDash's internal RL stack, RL environments built on real operational systems, training and evaluation pipelines, and agent evaluation harnesses, with engineering support to extend them as your research demands Direct access to leadership — a seat at the table for the decisions that shape the research org, with the autonomy to operate as a principal-level researcher Publication freedom — we expect and support publication at top venues (NeurIPS, ICML, ICLR, RSS, CoRL, KDD, etc.) with a fast, supportive internal review process Compute and data for external collaborators — budget to bring in academic collaborators, fellows, and visiting researchers as your agenda requires Research Areas We are broadly interested in researchers across the following areas, though the right candidate may reshape this list: Agentic systems for logistics and local commerce — long-horizon planning, tool use, multi-agent coordination, and evaluation methodologies for agents operating in physical-world marketplaces Memory and personalization — transfer RL, continual learning, harness-based improvements, and systems that adapt to individual consumers, merchants, and Dashers over time without catastrophic forgetting or unsafe drift Foundation models for marketplace dynamics — forecasting, pricing, matching, and personalization at marketplace scale, including domain-specific pre-training and post-training Evaluation and measurement — new benchmarks, eval harnesses, and methodologies for ML systems deployed in messy, real-world operational settings Multimodal understanding — vision, speech, and language applied to merchant catalogs, in-store and on-the-road imagery, and consumer interfaces Robotics and embodied AI for last-mile delivery — perception, planning, and learning systems for the physical edge of the marketplace Who We're Looking For A strong research track record: first-author publications at top ML venues, or equivalent demonstrated output (widely-used systems, influential open-source work, or research artifacts adopted at scale) Experience leading ambitious research projects end-to-end, from problem framing through to results that other people built on Taste: the ability to identify which problems are worth working on, when an approach is exhausted, and when a result is real A builder's instinct: comfortable working close to real systems and real data, not just on benchmarks Excitement about the founding-team aspects of the role: hiring, agenda-setting, culture-building, and partnering across functions Impact, you want to ship frontier systems to production and see your work being leveraged by hundreds of millions of consumers Excellent written and verbal communication, and a track record of mentoring or developing other researchers PhD in a relevant field is typical but not required. We weigh demonstrated research output and judgment far more heavily than credentials. Why Now DoorDash is at an inflection point: the company has the data, scale, capital, and operational reach to be one of the most important places in the world to do applied AI and foundational research, and we're committing to building the org that lives up to that. Founding researchers will have an outsized impact on what DoorDash AI Research becomes, and on what gets built on top of it. Notice Regarding Use of AI and Automated Tools: To streamline our hiring process, DoorDash utilizes an automated recruitment tool called Gem. How it works: Gem assists our recruiting team by evaluating job related qualifications and characteristics in connection with hiring. The tool is designed and used to support - rather than replace - human decision-making; trained personnel make final decisions with meaningful human review and oversight, and DoorDash does not use Gem or other AI-enabled tool in a manner that has the effect of subjecting applicants or employees to discrimination based on any protected characteristic or proxy or for engaging in any protected activity under applicable law. Data Retention, Privacy & Bias Audit: Data collected during this process is retained in accordance with our Candidate Privacy Policy and applicable state laws. In compliance with New York City Local Law 144, the independent bias audit summary for Gem is publicly available for review at our Careers Page . Compensation The 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 to all regular employees, which includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, commuter benefits match, paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act). DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others. To learn more about our benefits, visit our careers page here . See below for paid time off details: For salaried roles: flexible paid time off/vacation, plus 80 hours of paid sick time per year. For hourly roles: vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week). The national base pay range for this position within the United States, including Illinois and Colorado. $203,500 — $299,300 USD About DoorDash 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. Our Commitment to Diversity and Inclusion 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. Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only We used 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 provided Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023. We resumed using Covey Scout for Inbound again on June 29, 2024, and ceased using Covey Scout for Inbound on April 30, 2026. The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: getcovey.com . Beware of recruitment scams: DoorDash, Deliveroo, and Wolt will never ask you to pay money or share sensitive financial information during hiring — learn more about our legitimate recruiting process at Recruitment Scam Awareness - DoorDash .

Requirements

Must-haves

You should apply if you want to do ambitious, publishable research in an environment with the data, compute, and operational reach to actually deploy what you build.
Set the research agenda for one or more areas of DoorDash AI Research, in close collaboration with the founding team and leadership
Lead high-impact research projects end-to-end — from problem framing through publication and, where appropriate, production deployment
Help build the team — interview, recruit, and mentor researchers, engineers, and fellows joining the org
Shape the org's culture and operating model — how we publish, how we collaborate with product teams, how we balance open research with proprietary work
Partner across DoorDash with ML platform, product, and operations teams to identify the highest-leverage research bets and translate findings into real-world impact
What You'll Have Access To
Novel proprietary data at marketplace scale — logistics traces, merchant operations, consumer behavior, real-time supply and demand signals, and longitudinal data unavailable anywhere else
High compute budgets for training and inference, sized to support frontier-scale experimentation including large-model pre-training and post-training, RL training runs, and large-scale evaluation sweeps
Direct access to leadership — a seat at the table for the decisions that shape the research org, with the autonomy to operate as a principal-level researcher
Publication freedom — we expect and support publication at top venues (NeurIPS, ICML, ICLR, RSS, CoRL, KDD, etc.) with a fast, supportive internal review process
Compute and data for external collaborators — budget to bring in academic collaborators, fellows, and visiting researchers as your agenda requires
Research Areas
We are broadly interested in researchers across the following areas, though the right candidate may reshape this list:
Agentic systems for logistics and local commerce — long-horizon planning, tool use, multi-agent coordination, and evaluation methodologies for agents operating in physical-world marketplaces
Memory and personalization — transfer RL, continual learning, harness-based improvements, and systems that adapt to individual consumers, merchants, and Dashers over time without catastrophic forgetting or unsafe drift
Foundation models for marketplace dynamics — forecasting, pricing, matching, and personalization at marketplace scale, including domain-specific pre-training and post-training
Evaluation and measurement — new benchmarks, eval harnesses, and methodologies for ML systems deployed in messy, real-world operational settings
Multimodal understanding — vision, speech, and language applied to merchant catalogs, in-store and on-the-road imagery, and consumer interfaces
Robotics and embodied AI for last-mile delivery — perception, planning, and learning systems for the physical edge of the marketplace
Who We're Looking For
A strong research track record: first-author publications at top ML venues, or equivalent demonstrated output (widely-used systems, influential open-source work, or research artifacts adopted at scale)
Experience leading ambitious research projects end-to-end, from problem framing through to results that other people built on
Taste: the ability to identify which problems are worth working on, when an approach is exhausted, and when a result is real

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

airestmlgo

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Parental Leave

Wellness