Senior Causal ML Engineer for Production Systems

DoorDash; Los Angeles (CA); On-site; USD 170,000 - 230,000; Full time

Benefits offered by this job

401(k) matching

Paid parental leave (16 weeks)

Wellness benefits

Commuter benefits match

Paid time off and sick leave

Job summary

DoorDash is seeking a Causal Machine Learning Engineer to build the causal ML spine for a large-scale consumer marketplace across New Verticals. You will work with ML, Analytics, Product, and Engineering to productionize uplift models, counterfactual evaluation, and decisioning systems.

You will translate causal ideas into scalable production pipelines, connect experiments with observational data, and partner with econometrics leaders to apply advanced methods such as diff-in-diff, double ML,

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, or fintech.

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.
• Connect experimentation, observational data, and ML decisioning to enable faster, more reliable tradeoffs.
• Design surrogate metrics and early indicators to accelerate development while preserving marketplace health.

Skills

Causal inference

Econometrics

Experimentation

Production ML

Product intuition

Education

PhD or MS in a quantitative field (CS/Statistics/Econometrics)

Tools

Python

SQL

PyTorch/TensorFlow

Spark

Airflow

Job description

DoorDash is seeking a Causal Machine Learning Engineer to build the causal ML spine for a large-scale consumer marketplace across New Verticals. You will work with ML, Analytics, Product, and Engineering to productionize uplift models, counterfactual evaluation, and decisioning systems.

You will translate causal ideas into scalable production pipelines, connect experiments with observational data, and partner with econometrics leaders to apply advanced methods such as diff-in-diff, double ML,