DoorDash
Machine Learning Engineer, Supply Strategy & Optimization
DoorDash, San Francisco, California, United States, 94199
Machine Learning Engineer, Supply Strategy & Optimization
About The Team
The Supply Strategy and Optimization team ensures DoorDash’s marketplace remains balanced, efficient, and profitable by intelligently managing Dasher supply and engagement. Our mission is to deliver an exceptional customer experience by keeping roads well‑supplied across all geographies and delivery verticals—while enabling Dashers to maximize their earnings and achieve supply outcomes efficiently.
We build systems that forecast supply needs, optimize incentive spend, and enable data‑driven decisions across dasher acquisition, retention, and mobilization. The team combines machine learning, optimization, and causal inference to design scalable levers and real‑time systems that balance Dasher supply with customer demand across geographies and delivery types.
About The Role
As a Machine Learning Engineer on the team, you’ll design and deploy production ML systems that drive decision‑making across Dasher acquisition, incentives, and marketplace balancing. You’ll own the end‑to‑end ML lifecycle—from feature engineering and model training to deployment, experimentation, and monitoring—while working closely with partners in Product, Operations, and Analytics to shape how DoorDash optimizes supply and mobilization at scale.
Key Initiatives You’ll Contribute To
Causal inference modelling to measure the incremental impact of Dasher acquisition and incentive strategies.
Incentive optimisation frameworks that personalise pay structures and improve efficiency.
Budget allocation and forecasting models that identify optimal spend across acquisition, referrals, and retention.
Platformisation of ML systems to standardise forecasting, monitoring, and experimentation at scale.
What You’ll Do
Own and operate ML systems that predict Dasher supply, optimise advertising spend, and improve marketplace balance.
Build optimisation and causal inference models to improve incentive efficiency and retention.
Develop automated experimentation pipelines for evaluating incentive performance and marketplace interventions.
Collaborate cross‑functionally to deliver scalable, production‑grade ML solutions.
Advance personalization frameworks that deliver targeted and adaptive Dasher incentives.
Enhance ML platformisation efforts to improve scalability and reliability across use cases.
Shape the future of supply optimisation and Dasher incentives at DoorDash.
Who We’re Looking For
PhD or 2+ years of industry experience post‑graduate degree developing advanced machine learning models with business impact.
Hands‑on experience owning production ML models and pipelines.
Strong fundamentals in applied machine learning, optimisation, and experiment design.
Thrives in ambiguous, fast‑paced environments and is motivated by measurable impact.
Track record of collaborating with cross‑functional partners and operating with end‑to‑end ownership.
Passionate about using ML to solve high‑impact, real‑world problems.
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 localised according to an employee’s work location. In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.
Pay ranges for U.S. locations (illustrative): • I4: $137,100—$201,600 USD • I5: $167,800—$246,800 USD • I6: $203,500—$299,300 USD
Benefits DoorDash cares about you and your overall well‑being. We offer a comprehensive benefits package to all regular employees, including 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, medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family‑forming assistance, a mental health program, and more.
Seniority Level Mid‑Senior level
Employment Type Full‑time
Job Function Engineering and Information Technology
Industry Software Development
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. 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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The Supply Strategy and Optimization team ensures DoorDash’s marketplace remains balanced, efficient, and profitable by intelligently managing Dasher supply and engagement. Our mission is to deliver an exceptional customer experience by keeping roads well‑supplied across all geographies and delivery verticals—while enabling Dashers to maximize their earnings and achieve supply outcomes efficiently.
We build systems that forecast supply needs, optimize incentive spend, and enable data‑driven decisions across dasher acquisition, retention, and mobilization. The team combines machine learning, optimization, and causal inference to design scalable levers and real‑time systems that balance Dasher supply with customer demand across geographies and delivery types.
About The Role
As a Machine Learning Engineer on the team, you’ll design and deploy production ML systems that drive decision‑making across Dasher acquisition, incentives, and marketplace balancing. You’ll own the end‑to‑end ML lifecycle—from feature engineering and model training to deployment, experimentation, and monitoring—while working closely with partners in Product, Operations, and Analytics to shape how DoorDash optimizes supply and mobilization at scale.
Key Initiatives You’ll Contribute To
Causal inference modelling to measure the incremental impact of Dasher acquisition and incentive strategies.
Incentive optimisation frameworks that personalise pay structures and improve efficiency.
Budget allocation and forecasting models that identify optimal spend across acquisition, referrals, and retention.
Platformisation of ML systems to standardise forecasting, monitoring, and experimentation at scale.
What You’ll Do
Own and operate ML systems that predict Dasher supply, optimise advertising spend, and improve marketplace balance.
Build optimisation and causal inference models to improve incentive efficiency and retention.
Develop automated experimentation pipelines for evaluating incentive performance and marketplace interventions.
Collaborate cross‑functionally to deliver scalable, production‑grade ML solutions.
Advance personalization frameworks that deliver targeted and adaptive Dasher incentives.
Enhance ML platformisation efforts to improve scalability and reliability across use cases.
Shape the future of supply optimisation and Dasher incentives at DoorDash.
Who We’re Looking For
PhD or 2+ years of industry experience post‑graduate degree developing advanced machine learning models with business impact.
Hands‑on experience owning production ML models and pipelines.
Strong fundamentals in applied machine learning, optimisation, and experiment design.
Thrives in ambiguous, fast‑paced environments and is motivated by measurable impact.
Track record of collaborating with cross‑functional partners and operating with end‑to‑end ownership.
Passionate about using ML to solve high‑impact, real‑world problems.
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 localised according to an employee’s work location. In addition to base salary, the compensation for this role includes opportunities for equity grants. Talk to your recruiter for more information.
Pay ranges for U.S. locations (illustrative): • I4: $137,100—$201,600 USD • I5: $167,800—$246,800 USD • I6: $203,500—$299,300 USD
Benefits DoorDash cares about you and your overall well‑being. We offer a comprehensive benefits package to all regular employees, including 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, medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family‑forming assistance, a mental health program, and more.
Seniority Level Mid‑Senior level
Employment Type Full‑time
Job Function Engineering and Information Technology
Industry Software Development
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. 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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