Senior Causal ML Engineer – Production Systems

DoorDash; Seattle (WA); On-site; USD 204,000 - 299,000; Full time

Benefits offered by this job

401(k) with employer matching

Paid parental leave

Medical, dental, and vision benefits

Job summary

DoorDash is hiring a Causal Machine Learning Engineer to build the causal ML foundation behind how DoorDash grows New Verticals. You will join a senior pod of causal ML and econometrics experts, shaping decisions across ranking, promotions, and marketplace interventions.

You will design production causal systems, uplift models, and counterfactual evaluations, collaborating with ML, analytics, product, and engineering teams to drive measurable impact.

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 ML engineering ability: build reliable pipelines, train models, evaluate them rigorously, and partner with platform teams to productionize.

Responsibilities

• Design, build, and productionize causal ML systems that influence 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.
• Connect experimentation, observational data, and ML decisioning to enable better tradeoffs when randomized experiments are slow or noisy.
• Design surrogate metrics and early indicators to accelerate decision-making without sacrificing long-term health.
• Collaborate with econometrics and analytics leaders to choose methods (doubly robust, IV, diff-in-diff, synthetic controls, double ML, CUPED, etc.).
• Translate causal models into production systems shaping ranking, targeting, budget allocation, and growth.
• Raise the bar for causal reasoning across ML teams and how to debug claims in production.

Skills

Causal inference

Econometrics

Experimentation

Causal ML

Production models

ML engineering

Cross-functional

Product judgment

Job description

DoorDash is hiring a Causal Machine Learning Engineer to build the causal ML foundation behind how DoorDash grows New Verticals. You will join a senior pod of causal ML and econometrics experts, shaping decisions across ranking, promotions, and marketplace interventions.

You will design production causal systems, uplift models, and counterfactual evaluations, collaborating with ML, analytics, product, and engineering teams to drive measurable impact.