Benchling

Benchling

Product Manager, Growth, Scientific AI Models

San Francisco, CA

Sponsorship not specifiedDetected 14 days ago
Machine LearningAgentic AIA/B TestingProduct ManagementProduct Strategy

About the role

  • You'll split your time between talking with customers to understand their needs and gather feedback, and managing product definition and execution to bring the products they want to life.
  • It's early days for scientific AI models, both at Benchling and in the industry at large.
  • We'll win if we stay curious and obsess over our customers.

Responsibilities

  • Own the product roadmap for our scientific model platform - defining and prioritizing the models, features, and capabilities that let scientists run inference fast, reliably, and cost-effectively across a diverse set of scientific models.
  • Help shape how we build AI at Benchling - driving experimentation, contributing to product and technical direction, and helping evolve our product development and go-to-market practices as the field matures.
  • you'll partner closely with engineering, legal, strategy, and sales/GTM to get cutting-edge scientific AI into the hands of the scientists who need it.
  • Scientific models (e.g. AlphaFold or Boltz2) predict structures, predict scientific, and generate new drug designs, acting as a design partner and a major time saver to scientists who are creating life-saving therapeutics.

Requirements

  • Technical fluency: you can read API specs, reason about system tradeoffs, and have credible conversations with engineers about how scientific models are built and served.
  • 5+ years of product management experience building technical or platform products, ideally in scientific, ML/AI, or other data-intensive domains.
  • Strong analytical skills, comfortable using data to drive product decisions and to measure and grow adoption and usage.
  • Collaborative mindset, able to work closely with engineers, scientists, and partners across legal, strategy, and GTM to bring new ideas to life.
  • This is an in-person team in San Francisco built around collaborating in the office in a fast-paced environment. We're in the office Monday through Friday.
  • Benchling welcomes everyone.
  • We believe diversity enriches our team so we hire people with a wide range of identities, backgrounds, and experiences.
  • We are an equal opportunity employer. That means we don't discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We also consider for employment qualified applicants with arrest and conviction records, consistent with applicable federal, state and local law, including but not limited to the San Francisco Fair Chance Ordinance.

Skills

  • When a breakthrough is delayed, the world waits.
  • Getting a molecule from discovery to patients, or a crop from lab to field, involves thousands of slow, manual, disconnected steps.
  • AI has the potential to change this, compressing decades of R&D work into years.
  • But that only happens when clean, structured scientific data and AI are built into how science gets done.
  • Benchling is the AI platform for biotech R&D.
  • Desire to work in a fast-paced environment, where priorities can shift and rapid experimentation is encouraged.

Company info

  • Work directly with customers to ideate use cases, gather feedback, and grow adoption and usage of our scientific AI models across scientific teams.
  • We'll rapidly iterate with customers and change directions quickly, figuring out new patterns for how we develop and go to market.
  • The Model Hub team is building a computational platform that provides access to cutting-edge scientific AI models to help scientists design better drugs.
  • As the growth-focused product manager on the team, you'll own the product execution of our scientific AI models products and features, including Model Hub, and drive how customers adopt and grow their usage of these models.

This listing is sourced directly from Benchling's careers page and normalized into a canonical job model.