Lead Causal ML Engineer — Value Metrics & Strategy

DoorDash, Inc.; New York (NY); On-site; USD 282,000 - 415,000; Full time

Benefits offered by this job

401(k) matching

Paid parental leave

Wellness benefits

Commuter benefits

Job summary

DoorDash is hiring a Principal Machine Learning Engineer to lead the Causal ML pod and establish the technical foundation for causal decisioning across products and marketplace actions.

You will define the company-level causal value metric, connecting experiments, observational data, and production ML to guide investments, prioritization, and governance while ensuring customer experience and marketplace health.

Qualifications

• 10+ years in causal inference, econometrics, experimentation, or causal machine learning.
• Experience leading design and productionization of causal models or measurement platforms.
• Deep judgement on randomized experiments, observational methods, and model-based decisioning.

Responsibilities

• Lead the Causal ML pod across strategy, architecture, and execution.
• Define and implement the company-level causal value metric and its framework.
• Build a decision system integrating experiments, observations, and models for product prioritization.

Skills

Causal inference

Econometrics

Experimentation

Causal ML

Productionalization

Decision engines

Long-term value reasoning

Job description

DoorDash is hiring a Principal Machine Learning Engineer to lead the Causal ML pod and establish the technical foundation for causal decisioning across products and marketplace actions.

You will define the company-level causal value metric, connecting experiments, observational data, and production ML to guide investments, prioritization, and governance while ensuring customer experience and marketplace health.