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Altos Labs

Biotech startup advancing cellular rejuvenation therapies

Director / Senior Director - Lab-in-the-Loop

Translational Research & Bench BiologyConfirmed live in the last 24 hours
Full-time$261.5k - $445.8kIn-person

About the Job

Requirements

  • A PhD or equivalent in genomics, systems biology, bioengineering, or a related discipline, with at least 10 years of post-PhD experience, including senior leadership roles.
  • Deep hands-on experience designing large-scale perturbation or functional genomics experiments for downstream computational modeling, rather than standalone biology.
  • Working fluency in machine learning concepts relevant to biological data, sufficient for substantive technical dialogue with machine learning leads.
  • A clear grasp of how experimental design choices determine what a model can learn from resulting data, and the judgment to design experiments accordingly.
  • Comfort exploring robotics and automation in wet labs, including areas at the edge of the candidate's expertise.
  • Sound judgment on build-versus-buy decisions for assays, tools, and models, plus direct experience managing contract research organizations and external vendor relationships.
  • Experience building, leading, and growing a technical team, alongside a track record of building or scaling experimental-computational feedback loops.
  • Demonstrated ability to lead and influence in a matrix organization, particularly aligning computational and experimental teams in different reporting lines.
  • Director or Senior Director-level seniority, combining people management with hands-on experimental design.
  • For Director: a PhD, at least 10 years of experience, a proven track record, and at least 4–5 years of people-management experience.
  • For Senior Director: a PhD, at least 14 years of experience, 7–8 or more years of people/team leadership, and broad experience driving multiple programs through multidisciplinary teams.

Responsibilities

  • Lead a team responsible for closed-loop experimental systems that generate data designed to train and validate large-scale foundation and hybrid models for biology.
  • Lead experimental verification of model outputs outside the iterative loop, including validating target hypotheses from the hybrid modeling program, and ensure results are rigorous enough to inform go/no-go decisions even when they do not directly retrain a model.
  • Partner directly with machine learning leads across multimodal predictive modeling, foundation model pretraining, and hybrid/mechanistic modeling to ensure model outputs—including in silico perturbation predictions and target hypotheses—are experimentally testable and experimental results efficiently improve model performance.
  • Architect and implement experimental designs for a machine-learning-first data-generation strategy, determining what to measure and at what scale and modality to reduce model uncertainty and verify and improve identifiability of hybrid/mechanistic models.
  • Identify and develop new in vitro and in vivo model systems to meet the longer-term needs of the Institute of Computational Biology's models, using the lab to generate scientifically valuable data.
  • Determine which tools, assays, and models to develop in-house versus source externally; manage contract research organization and external vendor relationships; and advise the Institute Director on experimental budget planning, balancing long-term innovation with immediate project requirements.
  • Set standards for experimental design, metadata capture, and automation so lab-generated data is maximally useful with machine learning in the loop, and mentor talent in this direction.
  • Act as the technical bridge between experimental and computational teams across the Institute of Computational Biology and partner Institutes.
  • Coordinate experimental priorities across the Institute of Computational Biology and partner Institutes in a matrixed environment where the role does not hold direct authority over all contributing teams.
  • Mentor the experimental team to work efficiently with computational partners in the Institute and foster cross-functional collaboration.

Desired Qualifications

  • Experience in robotics and automation in wet labs is welcomed, particularly in areas at the edge of the candidate's expertise.

About the Company

Altos Labs

Biotech startup advancing cellular rejuvenation therapies

Altos Labs focuses on cell rejuvenation research to restore cellular health and resilience, with the aim of reversing diseases, injuries, and disabilities by programming cells to resist stressors that cause illness. It advances biotech R&D in cellular rejuvenation, producing treatments that can be commercialized for healthcare providers or patients and likely collaborates with research institutions and pharma partners. Unlike purely diagnostic firms, Altos Labs centers on developing breakthrough cellular therapies and regenerative strategies grounded in research, seeking to improve long-term health outcomes. Its goal is to translate cellular rejuvenation science into practical treatments that extend healthspan and reverse disease processes.

Company size
501-1,000
Company stage
Early VC
Total funding
$3.3B
Headquarters
Redwood City, CA
Founded
2021

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