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Senior Scientist & Program Lead

Pear Vc

San Francisco Bay AreaPosted 18 h agoDirect from company

  • LocationSan Francisco Bay Area
  • Work typeNot stated
  • EmploymentFull-time
  • Posted28 October 2026
  • SourcePear Vc's careers page (Ashby)
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About the role

[https://app.ashbyhq.com/api/images/user-content/cca476c0-947e-4006-a2cb-409350de667a/bb75f4c6-41dd-465b-9ce2-cbce01b165d3/Screenshot%202026-10-28%20at%202.54.46%E2%80%AFPM.png]

SENIOR SCIENTIST & PROGRAM LEAD | ENZYMOLOGY

WHAT WE’RE BUILDING

Velocity Bio is a venture-backed startup spun out of Stanford University combining cutting-edge microfluidics with AI to accelerate discovery of next-generation therapeutics. We are building the world’s largest dataset of high-fidelity enzyme function to train AI models for allosteric drug discovery and accurate enzyme function prediction.

Recently, Velocity partnered https://www.linkedin.com/feed/update/urn:li:activity:7514071489558749185 with the Institute for Protein Design at the University of Washington, Argonne National Laboratory, and SLAC National Accelerator Laboratory on a Department of Energy Genesis Mission project to harness AI for breakthrough enzyme design. With our partners, we’re building the missing, massive quantitative datasets of activity and structure for computationally-designed enzymes needed to unlock next-generation AI models to design enzymes de novo with unprecedented fidelity.

YOUR IMPACT

In this role, you’ll work closely with the founding team on our mission to unlock AI models for allosteric drug discovery and accurate enzyme function prediction. To do this, you’ll scale large-scale, high-fidelity enzyme function datasets, develop novel in vitro enzyme assays on our proprietary microfluidic platform, and manage external collaborations. This role will combine hands-on wet-bench biochemistry, data generation and analysis on Velocity’s high-throughput platform, as well as leadership by managing internal and external projects. As an early hire, you’ll have significant opportunity to work with the founding team and shape the scientific direction and culture of Velocity.

THIS ROLE WILL INVOLVE

- Designing, performing, and analyzing high-throughput enzyme assays on Velocity’s platform

- Designing and managing large-scale internal/external data generation campaigns

- Developing new high-throughput classical quantitative biochemical assays

- Working closely with AI/ML engineers to guide model development and evaluations

- Shaping Velocity’s scientific roadmap alongside the founding team

REQUIRED QUALIFICATIONS

- PhD in life sciences (Biochemistry, Biophysics, Chemical Biology, or Structural Biology preferred)

- 3+ years of relevant industry experience

- Expertise in enzymology and in vitro functional assays

- Deep understanding of protein structure and function

- Fluent in common molecular biology techniques (construct design, cloning, DNA and protein purification, etc.)

- Fluent in Python programming

- Ability to move quickly between strategic planning and hands-on execution

- Exceptional scientific rigor and attention to detail

PREFERRED QUALIFICATIONS

- Experience leading large-scale internal/external projects

- Hands-on experience performing other protein biophysical assays characterizing stability, binding, etc.

- Experience performing recombinant protein expression and purification

- Experience with NGS workflows

THIS POSITION MIGHT BE A GOOD FIT IF YOU…

- Are passionate about working on problems with huge potential to improve human health

- Enjoy rigorous science and designing and performing complex biophysical experiments

- Are excited to shape an early startup and influence how we work and what we build

- Are highly organized and a self-directed learner

- Want to join a fast-paced, collaborative environment in the heart of the Bay Area

BENEFITS

- Competitive salary and equity

- Full health, dental, and vision insurance

- 401(k) plan

LOCATION

- In-person; MBC BioLabs in San Carlos, CA

- On-site parking available

- 10-minute walk from a Caltrain station

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