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Salary
≈ $83k – $226k per year (Estimated)
Location
In office (San Francisco)
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Jan 6, 2026. Becoming scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Becoming is an AI and robotics research company building developmental intelligence, models that predict how organisms change over time, starting with developmental biology. It develops robotic systems that sustain mammalian development outside the body and hires research scientists, stem cell biologists and optics engineers. The company is headquartered in San Francisco, California, United States.

About Becoming

Becoming is building Developmental Intelligence: AI for predicting how organisms change over time.

Development is intelligence in motion. Most experimental systems fail when metabolic demands become too high. We are building systems that don’t - combining engineered metabolic environments, longitudinal measurement, and predictive models to turn development into something that can be understood, tested, and controlled.

This is frontier tech with real stakes. We value speed, rigor, integrity, and ownership.

The Role

We are hiring a Developmental & Stem Cell Biology to own and scale critical biological systems within Becoming’s platform.

This is a high-agency, industry-caliber role. You will not be handed a task list. You will be expected to identify problems, propose solutions, and drive experiments from idea to impact. You will build and operate long-horizon developmental systems from stem and primary cells, integrate them with engineered environments, and generate data that directly informs platform decisions.

You will work closely with scientists, engineers, and AI researchers, with increasing ownership as the platform scales.

What You’ll Own

  • Design and execution of long-horizon developmental systems derived from stem and primary cells
  • Day-to-day ownership of biological performance: stability, progression, and reproducibility
  • Development of benchmarks and readouts for developmental state, patterning, and functional maturation
  • Execution of contextual perturbations (signaling, nutrients, mechanics, metabolic conditions) and interpretation of outcomes
  • Generation of clean, interpretable datasets suitable for modeling and decision-making
  • Iteration on protocols and systems to improve robustness, scalability, and reliability
  • Clear, direct communication of results, failures, and next steps across disciplines

Who You Are

You are someone who:

  • Operates with high agency - you take initiative and don’t wait to be told what to do
  • Takes ownership of outcomes, not just experiments
  • Brings high energy and momentum to ambitious scientific problems
  • Acts with high integrity - you are honest about data, limitations, and uncertainty
  • Communicates directly and clearly, especially when things aren’t working
  • Is self-aware and receptive to sharing and receiving feedback
  • Thinks like a systems integrator, connecting biology, environment, hardware, and data
  • Thrives in fast-moving tech environments where priorities evolve quickly

Requirements

Required

  • PhD (or equivalent experience) in developmental biology, stem cell biology, or a related field
  • At least 1 year of industry experience in tech, biotech, pharma, or a startup, with exposure to real-world timelines, cross-functional collaboration, and delivery expectations
  • Strong hands-on experience with stem cell-derived early developmental systems and/or mammalian developmental processes
  • Solid intuition for temporal dynamics and context-dependent biology
  • Demonstrated ability to take loosely defined goals and turn them into executed, decision-relevant experiments
  • Comfort making progress with incomplete information and iterating quickly

Strong Signals

  • Experience with mouse developmental systems, lineage progression, or early tissue organization
  • Prior work building or scaling new experimental systems, not just running established assays
  • Exposure to long-term cultures, perfusion, or engineered microenvironments
  • Interest in how biological data feeds into predictive or computational models

Benefits

  • Competitive salary and meaningful equity depending on experience level
  • Full benefits
  • High-trust, high-ownership environment
  • The opportunity to define a new scientific category from the ground up
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