Head of Causal ML & Value Platform

DoorDash; Sunnyvale (CA); On-site; USD 282,000 - 415,000; Full time

Benefits offered by this job

401(k) matching

Paid parental leave

Wellness benefits

Commuter benefits

Medical, dental and vision benefits

Job summary

DoorDash is seeking a Principal Machine Learning Engineer to lead the Causal ML pod and define the technical foundation for company‑level causal decisioning. You will set multi‑year direction, drive production-ready causal models, and translate complex evidence into clear, actionable decisions for product, growth, and marketplace teams.

You will work across experiments, observational data, and policy logs to build a durable measurement framework, enabling evidence-based prioritization and

Qualifications

• 10+ years in causal inference, econometrics, experimentation, or causal ML.
• Experience leading design and productionization of causal models and large-scale decision engines.
• Strong judgment on randomized experiments, observational methods, surrogate endpoints, and model-based decisions.

Responsibilities

• Define multi-year technical direction for causal ML and lead the pod’s portfolio and operating model.
• Build and validate a company-level causal value metric connected to experiments, observations, and production ML.
• Architect reusable causal capabilities for treatment effect estimation and counterfactual evaluation.

Skills

Causal inference

Production ML

Experimentation

Measurement platforms

Executive influencing

Job description

DoorDash is seeking a Principal Machine Learning Engineer to lead the Causal ML pod and define the technical foundation for company‑level causal decisioning. You will set multi‑year direction, drive production-ready causal models, and translate complex evidence into clear, actionable decisions for product, growth, and marketplace teams.

You will work across experiments, observational data, and policy logs to build a durable measurement framework, enabling evidence-based prioritization and