Principal Machine Learning Engineer, TEAM
About this role
Guiding the Causal ML pod involves establishing technical direction, shaping operating models, and staying hands-on with complex modeling tasks. The team builds causal decisioning systems for New Verticals like grocery, retail, and convenience, operating within dynamic marketplaces where every marketplace action raises a causal question. Leadership focuses on creating a company-level causal value metric, defining measurement frameworks, and architecting reusable capabilities for treatment effect estimation and counterfactual policy evaluation. Suited candidates bring deep technical judgment in causal inference, strong machine learning systems engineering capabilities, and a track record of influencing cross-functional leaders.
What you will do
- Lead the Causal ML pod across technical strategy, architecture, execution, and quality.
- Define the company-level causal value metric and its associated measurement framework.
- Build a decision system that teams utilize for product prioritization, experiment readouts, and budget allocation.
- Architect reusable causal capabilities for treatment effect estimation, surrogate validation, and counterfactual policy evaluation.
- Guide production applications spanning promotions, search, recommendations, and inventory-aware discovery.
- Set rigorous standards for validation, monitoring, reproducibility, and governance.
- Influence senior leaders across product, engineering, analytics, finance, and strategy through clear problem framing.
What you need
- Have extensive experience of 10 plus years in causal inference, econometrics, experimentation, or causal machine learning.
- Demonstrate a record of setting technical direction beyond a single team and leading the productionization of causal models.
- Show deep judgment regarding randomized experiments, observational methods, and surrogate endpoints.
- Display fluency with methods including doubly robust estimation, double machine learning, instrumental variables, and synthetic controls.
- Possess strong machine learning engineering and systems ability to shape data contracts, modeling pipelines, and serving patterns.
- Provide a track record of influencing executives and senior cross-functional partners through technical judgment and evidence.
Benefits
- 401(k) plan with employer matching
- 16 weeks of paid parental leave
- Wellness benefits and commuter benefits match
- Flexible paid time off and paid sick leave
- Medical, dental, and vision benefits
- Disability and basic life insurance
Skills and tech stack
Questions candidates ask
What is the salary range for this role?
The base salary ranges from $282,100 to $414,800 USD. Starting pay is determined by job-related factors including skills, experience, qualifications, and work location.
Where is the position located?
The role is located in San Francisco, CA; Sunnyvale, CA; Seattle, WA; and New York, NY. Base salary is localized according to the employee's work location.
What kind of benefits are included?
The benefits package includes a 401(k) plan with employer matching, 16 weeks of paid parental leave, medical, dental, and vision benefits, and flexible paid time off. Additional offerings cover wellness benefits, disability and basic life insurance, and a mental health program.