Sr. Data Scientist, GenAI & Labeling Platforms

PinterestSan Francisco, CA
$139,764 - $287,749Remote

About The Position

Pinterest is looking for candidates excited to be a part of its AI-driven mission to bring inspiration to millions. This role focuses on advancing the science and systems behind labeling, evaluation, and GenAI-enabled workflows. The work spans LLM-assisted labeling, human-in-the-loop quality systems, prompt and rubric design, model evaluation, and methods for improving the speed, consistency, and usefulness of judgment-based data. The company is seeking a strong senior individual contributor to execute high-impact technical work, partner cross-functionally to turn successful ideas into durable platform capabilities, and grow with the team as the space evolves.

Requirements

  • 6+ years of combined post-graduate academic and industry experience (or PhD + 3 years) applying scientific methods to real-world problems on large-scale data
  • Strong hands-on experience as an individual contributor solving technically complex, high-impact data science or ML problems
  • Experience applying LLMs or other generative AI techniques to practical workflows, systems, or products
  • Ability to turn ambiguous problems into rigorous analyses, experiments, and prototypes
  • Track record of writing high-quality code and using technical work to influence product or platform direction
  • Solid cross-functional collaboration skills and experience working effectively across teams
  • Business and product sense with the ability to define meaningful success metrics
  • Self-directed learning mindset and comfort working in a rapidly evolving technical landscape

Nice To Haves

  • Experience with labeling systems, evaluation frameworks, human judgment workflows, or internal AI tooling is strongly preferred

Responsibilities

  • Execute high-impact scientific work across GenAI-powered labeling and evaluation systems
  • Identify opportunities where LLMs and related methods can improve quality, speed, coverage, and cost efficiency
  • Develop prototypes that demonstrate value in areas such as prompt optimization, task decomposition, quality estimation, routing, and human-in-the-loop workflows
  • Design experiments and measurement frameworks to evaluate model performance, workflow outcomes, and operational tradeoffs
  • Partner with engineering, product, and data science teams to productionize successful approaches
  • Apply standards for trustworthiness, including bias measurement, calibration, quality control, and responsible oversight
  • Contribute to reusable methods and frameworks that can scale across teams and use cases
  • Support more junior scientists and contribute to the technical health of the team

Benefits

  • Equity
  • Information regarding the culture at Pinterest and benefits available for this position can be found here.
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