Product Management Lead

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

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401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$102,662 U.S. median for this role

Projected growth (BLS Employment Projections)

+5.4% - Faster than average

Matched to SOC 11-1021 - Product Management aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Product From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Work mode

Remote From the posting source checked Jun 20, 2026

In-office days

0 days From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Company stage

Growth-stage From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Product Management Lead San Mateo, CA, New York, NY, Remote, San Diego, CA Genesis Molecular AI is pioneering a transformative approach to drug discovery by leveraging state-of-the-art machine learning, computational chemistry, and biology. Our mission is to accelerate the development of life-changing therapies by merging cutting-edge technology with innovative science. We are building a world-class team to drive forward the future of drug discovery. About the Team: We are a mission-driven group of scientists and engineers using cutting-edge computational methods to discover drugs for unmet medical needs. Our work spans machine learning, computational chemistry, biology, and wet lab experimentation , all operating within a high-trust, deeply technical environment. You'll join a team with extremely strong ML talent that is actively pushing the frontier of AI in drug discovery . We are refining how experimental data, biological context, and computational models integrate into a seamless feedback loop. You will help reshape how data flows from experiment → infrastructure → model → decision and increase the speed and scale at which we learn. The Role This is a builder-integrator role inside a deeply technical, cross-domain environment spanning AI/ML, engineering, computational chemistry, biology, and wet lab operations. You will serve as the connective tissue and acceleration engine across these domains. You will work closely with senior leadership to own roadmap definition and execution across critical internal platforms while driving structural improvements in how our teams operate. This role exists to: - Bridge domain silos and reduce friction between ML experimentation and biological context

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