Member of Technical Staff — Research, Operations & Decision Science

We look for domain experts who are excited to tackle unsolved problems. A prediction matters most when it leads to better decisions — and evaluating decision quality in high-stakes operational environments is a challenge on its own. Your mission is to bring that discipline to our reasoning research: defining the objectives our models optimize toward and the methods by which we judge whether their decisions are actually good.

Responsibilities

- Formulate the objectives, constraints, and decision problems that our reasoning models optimize toward

- Develop methodology for evaluating decision quality under uncertainty, including counterfactual reasoning about outcomes

- Translate the realities of complex operational environments into well-posed optimization and decision problems

- Bring rigor to how optimization and decision-making models are validated for real-world use

- Partner with reasoning, evaluation, and product teams to connect research to the decisions it ultimately informs

What we're looking for

We value a relentless approach to problem-solving, rapid execution, and the ability to quickly learn in unfamiliar domains.

- 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