Member of Technical Staff — Research, Operations & Decision Science
On-siteSan Francisco, California, United States
Job Summary
Formulate objectives, constraints, and decision problems for reasoning models optimizing toward specific outcomes. Develop methodologies to evaluate decision quality under uncertainty, incorporating counterfactual reasoning about potential outcomes. Translate complex operational realities into well-posed optimization and decision problems while bringing rigor to model validation for real-world use. Partner with reasoning, evaluation, and product teams to connect research directly to the decisions it informs. This role requires a PhD in operations research or decision science and experience in high-stakes environments where forecasts drive consequential actions.
Required Qualifications
- Deep expertise in operations research, decision science, or a closely related field (typically a PhD or equivalent experience)
- Strong grasp of optimization and decision-making under uncertainty, ideally including stochastic methods
- Experience in high-stakes operational settings where forecasts drive consequential decisions
- Particular strength in evaluating the quality of optimization or decision models, not just building them
- Ability to collaborate closely with ML researchers and translate operational realities into technical problems
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