Full-Time

Optics Engineer

Becoming

Becoming

11-50 employees

AI-guided closed-loop mammalian development systems

No salary listed

San Francisco, CA, USA

In Person

Bachelor's

Category
Hardware Engineering (2)
,

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Requirements
  • Have built optical systems that operated outside of controlled lab demos.
  • Understand how optical decisions impact mechanical tolerances and electrical noise.
  • Have a degree in optics, physics, electrical engineering, or equivalent demonstrated depth.
  • Have experience designing and shipping integrated optical systems.
  • Have a strong first-principles understanding of optical design and detection physics.
  • Have experience integrating optics with mechanical and electrical platforms.
  • Demonstrate ownership of systems operating under real-world constraints.
  • Be able to operate without rigid process scaffolding or heavy vendor abstraction.
Responsibilities
  • Own optical subsystems end to end inside complex hardware platforms.
  • Architect optical paths including illumination, detection, filtering, and signal optimization.
  • Select components with attention to stability, lifecycle, and manufacturability.
  • Integrate optical systems mechanically and define alignment strategies under thermal and environmental constraints.
  • Integrate detectors and signal acquisition systems electrically.
  • Optimize signal-to-noise ratio and mitigate drift.
  • Develop calibration frameworks and validate long-term stability.
  • Prototype, stress-test, and perform failure analysis.
  • Define documentation and standards that enable scaling.
  • Define specifications, make architecture decisions, and own real-world outcomes.
  • Debug signal degradation in live systems and assess whether signal performance holds over time.

Becoming.ai builds robotic systems with closed-loop metabolic control to sustain mammalian development outside the body, paired with AI models that learn how development unfolds under different interventions. Its core hardware delivers nutrients, removes waste, and controls gas exchange in real time, creating a controllable environment for long-running developmental data. The AI analyzes this data to predict developmental trajectories and identify interventions that shift outcomes, enabling virtual organism models. The company differentiates itself by combining hardware-enabled metabolic exchange with dynamical AI models to generate and study controlled developmental data over extended periods, rather than just analyzing static biological samples. Its goal is to enable long-term, predictable developmental studies that can inform regenerative medicine, drug discovery, and fundamental developmental biology.

Company Size

11-50

Company Stage

N/A

Total Funding

N/A

Headquarters

N/A

Founded

2023

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Simplify Jobs

Simplify's Take

What believers are saying

  • The July 2026 site says the system learns from real experiments in real time.
  • June 2026 career posts show demand for robotics, bioinformatics, and dynamical-systems talent.
  • If validated, developmental intelligence could reshape regenerative medicine and drug discovery workflows.

What critics are saying

  • No 2026 funding, customers, or revenue announcements signal a pre-commercial science project.
  • July 2026 hiring for research scientists and bioinformatics engineers signals heavy technical dependency and runway burn.
  • If external mammalian development stalls, the core platform collapses before any defensible dataset exists.

What makes Becoming unique

  • Becoming.ai pairs closed-loop robotic metabolism with predictive models for developmental futures.
  • Its July 2026 website claims sustained mammalian development generates training data for virtual organisms.
  • Founder Divya Dhar Cohen has led the company since January 2023 in San Francisco.

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Benefits

Company Equity

Growth & Insights

Headcount

6 month growth

-17%

1 year growth

-17%

2 year growth

-17%