Staff Causal ML Engineer: Production Uplift & Decisioning

DoorDash USA; United States; Remote; USD 204,000 - 299,000; Full time

Benefits offered by this job

401(k) plan with employer matching

16 weeks of paid parental leave

Wellness benefits

Commuter benefits match

Paid time off and paid sick leave

Medical, dental, and vision benefits

11 paid holidays

Disability and basic life insurance

Family‑forming assistance

Mental health program

Job summary

DoorDash is hiring a Causal Machine Learning Engineer to build the causal spine for a large-scale consumer marketplace within New Verticals. You will join a senior team to design, implement, and productionize uplift models, heterogeneous treatment effects, and counterfactual evaluation frameworks.

The role requires deep expertise in causal inference, econometrics, experimentation, and production systems, collaborating across ML, analytics, product, and engineering teams to influence real

Qualifications

• Deep practical experience with causal inference, econometrics, experimentation, or causal ML.
• Experience shipping models or decision systems in production, ideally in consumer marketplaces, ads, recommendations, search, pricing, promotions, logistics, fintech, or other high‑scale settings.
• Strong judgment around tradeoffs between randomized experiments, observational estimation, and model‑based decisioning.

Responsibilities

• Design, build, and productionize causal ML systems that influence real marketplace decisions across New Verticals.
• Build uplift / heterogeneous treatment effect models for consumer lifecycle value, promotions, retention, and reactivation.
• Develop counterfactual evaluation frameworks for ranking, recommendations, search, promotions, substitutions, and marketplace interventions.

Skills

causal inference

experimentation

causal ML

ML engineering

production systems

business judgment

cross-functional collaboration

Job description

DoorDash is hiring a Causal Machine Learning Engineer to build the causal spine for a large-scale consumer marketplace within New Verticals. You will join a senior team to design, implement, and productionize uplift models, heterogeneous treatment effects, and counterfactual evaluation frameworks.

The role requires deep expertise in causal inference, econometrics, experimentation, and production systems, collaborating across ML, analytics, product, and engineering teams to influence real