Sr. Staff Data & Applied Scientist, GenAI & Labeling Platforms

Pinterest • Palo Alto, CA

6d • Remote

About The Position

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
Pinterest brings millions of people the inspiration to create a life they love. To evolve this mission our product and engineering teams need to innovate. Advancements in Generative AI have opened up a wealth of opportunities for improvements in productivity, and we’ve only scratched the surface of its capabilities in the prompting and labeling space. Early results show strong promise for the role it can play in these tasks, reducing the time and cost of our labeling efforts, focusing our surveys and human rater efforts on higher value problems, and improving the accuracy of our learnings.
This role focuses on advancing the science and systems behind labeling, evaluation, and GenAI-enabled workflows. The work spans areas such as 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.
We’re looking for an accomplished senior individual contributor to lead high-impact technical work in this space. This person will drive foundational innovations, prototype new capabilities, establish rigorous evaluation approaches, and partner cross-functionally to turn successful ideas into durable platform capabilities.

Requirements

• 10+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on large-scale data
• Deep hands-on experience as an individual contributor solving technically complex, high-impact data science or ML problems
• Strong experience applying LLMs or other generative AI techniques to practical workflows, systems, or products
• Demonstrated ability to turn ambiguous problems into rigorous analyses, experiments, prototypes, and scalable solutions
• Proven track record of writing high-quality code and using technical work to influence product or platform direction
• Strong cross-functional collaboration skills and a track record of influencing leaders and peers through data and technical judgment
• Strong business and product sense with the ability to define meaningful success metrics and prioritize high-value opportunities
• 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

• Drive 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 rigorous measurement frameworks to evaluate model performance, workflow outcomes, and operational tradeoffs
• Partner with engineering, product, and data science teams to shape roadmaps and productionize successful approaches
• Establish strong standards for trustworthiness, including bias measurement, calibration, quality control, and responsible oversight
• Create reusable methods and frameworks that can scale across teams and use cases
• Mentor other scientists and contribute technical leadership across the organization

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 501-1,000 employees