Job Details

Staff Machine Learning Engineer - Ads Economics

  2025-11-28     DoorDash USA     San Francisco,CA  
Description:

San Francisco, CA; Sunnyvale, CA

About the Team

The mission of the Ads Economics team is to ensure we maintain a healthy ads marketplace across all our verticals for both search (query context) and discovery experiences while fulfilling the requirements of all players in this marketplace.

Ads Economics is a critical part of the Ads Delivery funnel with a broad charter responsible for Bidding, Auction Design, Budget Pacing, Forecasting, and Ads Experimentation. Our work directly shapes advertiser experience, consumer experience, and marketplace balance. We leverage artificial intelligence and advanced ML, deep learning techniques to power decision‑making in real time — from optimizing ad auctions to generating the most efficient bids and pacing budgets dynamically. These models sit at the heart of DoorDash's ad delivery and play a pivotal role in improving the efficiency, fairness, and scalability of our marketplace.

The opportunity is massive as DoorDash expands into new verticals like Grocery and Retail while building unique innovative ad products to leverage the closed‑loop marketplace.

About the Role

We're looking for a Staff Machine Learning Engineer to serve as the technical lead driving the design and development of large‑scale ML/optimization systems within the Ads Delivery funnel.

Responsibilities

  • Lead the technical design and implementation of ML solutions for key Ads Economics areas such as Auction, budget pacing, bidding optimization, and forecasting.
  • Partner closely with Product, Data Science, and Engineering teams to design experiments, model frameworks, and production ML systems that directly impact advertiser ROI and marketplace efficiency.
  • Provide technical mentorship and guidance to engineers and cross‑functional partners — leading through influence, not management.
  • Build and deploy 0→1 ML systems that improve ad delivery outcomes and marketplace health.
  • Set best practices for model training, evaluation, deployment, and monitoring.
  • Act as a technical thought leader for Ads ML — influencing roadmap, experimentation design, and overall Ads system evolution.

You're excited about this opportunity because you will…

  • Own impactful ML systems: Build and improve models that directly have a large impact on top and bottom line financials.
  • 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: We're one of the fastest growing Ads platforms in the world and we're looking to take that even further.

We're excited about you because you have…

  • M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, or a related field.
  • 8+ years of industry experience building production‑scale ML systems.
  • Expertise in at least one of: auction design, pacing, bidding optimization, or forecasting.
  • Strong understanding of probability theory, statistics, and machine learning fundamentals.
  • Proven ability to lead cross‑functional initiatives and drive complex technical projects end‑to‑end.
  • Excellent communication skills — able to explain technical concepts to product, business, and engineering audiences.
  • Experience in Ads or marketplace systems is a plus.

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.

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).

National Base Pay Ranges (United States, including Illinois and Colorado)

  • $137,100 – $201,600 USD
  • $167,800 – $246,800 USD
  • $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 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.

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