Machine Learning Engineer, Dasher Earnings

About the Team

Our mission is to maximize earning opportunities for Dashers in a way that’s financially sustainable for DoorDash. We’re building systems that ensure every Dasher can achieve their financial goals—whether that means paying rent, saving for a dream, or simply earning extra cash—no matter what kind of delivery they complete.

We measure our success by improving earning potential and reliability, making pay feel fairer and more consistent, and continuously finding new ways to help both Dashers and DoorDash thrive. We believe in building a pay platform that is thoughtful, protects our Dashers, and supports the goals of all DoorDash teams.

Our north star:

• DoorDash is a profitable and reliable way for every Dasher to earn money
• Every Dasher can achieve their financial goals
• Our pay system is both fair for Dashers and sustainable for the business

About the Role

As an ML Engineer in Dasher Earnings, you’ll lead the design and deployment of models with direct and measurable business impact. You’ll drive the full ML lifecycle: feature creation, model development, deployment, experimentation, and monitoring. You’ll also work closely with cross-functional partners in product, operations, and analytics.

Key initiatives you’ll contribute to:

• Evolving our pay models to maximize marketplace efficiency, fairness, and Dasher engagement
• Advancing causal inference and optimization frameworks for live experiments (including hourly switchbacks, A/Bs)
• Automating and scaling our model deployment and monitoring processes

You can find out more on our ML blog here

You’re excited about this opportunity because you will…

• Own impactful ML systems: Build and improve models that drive Dasher earnings, retention, and business growth
• Drive experimentation: Rapidly test hypotheses via robust sequential experiments; measure and explain your models’ impact on marketplace KPIs
• Optimize at scale: Work with one of the largest delivery datasets, building optimization pipelines that consider budget, fairness, assignment rates, and more
• Collaborate cross-functionally: Partner with engineering, analytics, product, and operations to iterate quickly, moving models from prototype to production
• Shape the future: Help define the direction of pay optimization and driver incentives across DoorDash

We’re excited about you because…

• 1+ years of industry experience post PhD or 3+ years of industry experience post graduate degree of developing advanced machine learning models with business impact.
• You have hands-on experience owning production ML models and pipelines
• You have strong fundamentals in applied machine learning, optimization, and experiment design
• You thrive in ambiguous, fast-paced environments and are motivated by measurable impact
• You have a track record of collaborating with cross-functional partners and operating with end-to-end ownership
• You’re passionate about using ML to solve high-impact, real-world problems

 

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

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 ranges for this position within the United States, including Illinois and Colorado.

I4$137,100—$201,600 USDI5$167,800—$246,800 USDI6$203,500—$299,300 USDAbout 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 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.

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.