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Salary: USD 265,400 - 445,800 / annual
Altos Labs is seeking a Director or Senior Director-level scientist to lead the lab-in-the-loop initiative, bridging experimental biology and machine learning. The company's mission is to restore cell health and resilience through cell rejuvenation to reverse disease and injury.
In this role, you will own the critical feedback loop between laboratory experiments and ML model development across in vitro and in vivo systems. You'll lead a team responsible for designing closed-loop experimental systems that generate purpose-built data to train and validate large-scale foundation and hybrid models for biology. You'll also lead experimental verification of model outputs outside the iterative loop—such as validating target hypotheses—ensuring results are rigorous enough to inform go/no-go decisions.
Key responsibilities include:
- Leading a team responsible for closed-loop experimental systems that generate data for training and validating large-scale foundation and hybrid models
- Leading experimental verification of model outputs, ensuring rigor for strategic decision-making
- Partnering with ML leads across multimodal predictive modeling, foundation model pretraining, and hybrid/mechanistic modeling to ensure model outputs are experimentally testable and results feed back efficiently
- Architecting innovative experimental designs targeting ML-first data generation strategies: determining what to measure, at what scale and modality, to most efficiently reduce model uncertainty and improve model identifiability
- Identifying and developing new in vitro and in vivo model systems to meet longer-term needs, treating the lab as a lever for generating scientifically valuable data
- Determining which tools, assays, and models should be developed in-house versus sourced externally; managing CRO and vendor relationships
- Setting standards for experimental design, metadata capture, and automation so lab-generated data is maximally useful with ML in the loop
- Acting as the technical bridge between experimental and computational teams across institutes
- Leading effectively in a matrixed environment, coordinating priorities across institutes without direct authority over all teams
You will work at the intersection of wet-lab biology and computational science, pushing the envelope of lab-in-the-loop workflows in an emerging, high-impact area.
REQUIREMENTS:
- PhD (or equivalent) in genomics, systems biology, bioengineering, or related discipline, with 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
- Working fluency in ML concepts relevant to biological data, sufficient for substantive technical dialogue with ML leads
- Clear grasp of how experimental design choices determine what a model can learn from resulting data
- Out-of-box thinking and strategic leadership in lab-in-the-loop for ML workflows; comfort exploring robotics and automation at the edge of expertise
- Sound judgment on build-vs-buy decisions for assays, tools, and models; direct experience managing CROs and vendor relationships
- Experience building, leading, and growing technical teams; track record of building or scaling experimental-computational feedback loops
- Demonstrated ability to lead and influence in matrix organizations, particularly aligning computational and experimental teams across reporting lines
- Director/Senior Director-level seniority with ability to manage people and stay hands-on with experimental design
For Director level: PhD + 10+ years experience with proven track record, minimum 4–5 years in people management.
For Senior Director level: PhD + 14+ years experience, 7–8+ years of people/team leadership, demonstrable broad background driving multiple programs through multidisciplinary teams.
