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Research Scientist

Latent - San Francisco | OnSite

Posted Jun 10, 2026

Benefits

Parental leave
Not verified
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)
$116,543 U.S. median for this role
Projected growth (BLS Employment Projections)
+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

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

Role

Role function
Engineering From the posting source checked Jun 20, 2026
Seniority
Mid From the posting source checked Jun 20, 2026
Work mode
Onsite From the posting source checked Jun 20, 2026
In-office days
5 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
Series A 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

Research Scientist San Francisco | OnSite RESEARCH SCIENTIST ABOUT LATENT HEALTH Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family. For everyone else, care is fragmented and impersonal. Medical history is scattered across systems that don't communicate. Physicians have minutes to understand decades of context. And when something goes wrong, patients are left with tools that understand medicine broadly-but not the individual. We believe this can be fundamentally rebuilt. At Latent Health, we are building systems that understand both: - the population (clinical knowledge at scale) - and the individual (longitudinal patient history) Our models are designed to answer complex clinical questions with patient-specific context and verifiable reasoning. Our dataset represents one of the most clinically diverse populations in the United States, including patients with chronic illness and complex disease. Each patient record contains extraordinary depth. ML AT LATENT HEALTH The Machine Learning team is responsible for building systems that run in real clinical workflows. We work on: - Verifiable reinforcement learning at scale - Mid-training and post-training of foundation models - Novel objectives derived from longitudinal patient data We are a small group of researchers and engineers focused on pushing the frontier while shipping real systems into production. We are a small team and expect engineers to take ownership of critical systems, not components. THE ROLE As a Machine Learning Engineer, Research, you will own the design and development of novel modeling approaches that advance state-of-the-art

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