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

The rate limit on ML for biology is rarely the model. It is the loop between what the lab measures and what the model needs. Altos is looking for a Director or Senior Director-level scientist to own that loop across in vitro and in vivo systems: closed-loop systems where predictions steer the next experiment and results retrain the model, and rigorous standalone verification of model outputs where the wet-lab design still has to hold up. As IoC's ML-for-biology programs scale, the loop between experimental design and model development becomes an increasingly critical driver of progress — the tighter that loop, the faster and more reliably we can improve both. We're looking for a leader who will push the envelope of the lab-in-the-loop with deep expertise in wet-lab biology and machine learning.

Responsibilities:

• Lead a team responsible for closed-loop experimental systems that generate data purpose-built to train and validate large-scale foundation and hybrid models for biology.
• Lead experimental verification of model outputs that fall outside the tight iterative loop — for example, validating target hypotheses from the hybrid modeling program — ensuring these results are rigorous enough to inform go/no-go decisions even when they don't directly retrain a model.
• Partner directly with ML leads across multimodal predictive modeling, foundation model pretraining, and hybrid/mechanistic modeling efforts to ensure model outputs — including in silico perturbation predictions and target hypotheses — are experimentally testable, and that experimental results feed back efficiently to improve model performance.
• Architect and implement innovative experimental designs that target a ML-first data generation strategy: what to measure, at what scale and modality, to most efficiently reduce model uncertainty, verify and improve identifiability of hybrid/mechanistic models.
• Look strategically beyond current needs to identify and develop new in vitro and in vivo model systems required to meet the longer-term needs of IoC's models — treating the lab not just as infrastructure to operate, but as a lever for generating the most scientifically valuable data possible.
• Determine which tools, assays, and models should be developed in-house versus sourced externally; manage relationships with CROs and external vendors where outsourcing is the right call; Provide strategic guidance to 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 ML in the loop, and mentor talent in this direction.
• Act as the technical bridge between experimental and computational teams across IoC and partner Institutes.
• Lead effectively in a matrixed environment, coordinating experimental priorities across IoC and partner Institutes where you don't hold direct authority over all contributing teams; Mentor the experimental team to work efficiently with the computational partners in the institute, fostering seamless cross-functional collaboration. 

• PhD (or equivalent) in a relevant field - genomics, systems biology, bioengineering, or a 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, not as standalone biology.
• Working fluency in ML concepts relevant to biological data, sufficient for substantive technical dialogue with ML leads.
• A clear grasp of how choices in experimental design determine what a model can and cannot learn from the resulting data — and the judgment to design experiments accordingly.
• An out-of-box thinker and a strategic leader in the emerging area of lab-in-the loop for ML workflows and discovery. Be comfortable with exploring areas of robotics and automation in wet-labs that are at the edge of your expertise. 
• Sound judgment on build-vs-buy decisions for assays, tools, and models, plus direct experience managing CROs 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 that may sit in different reporting lines.
• Director/Sr. Director-level seniority — someone who can both manage people and stay hands-on with experimental design.

Minimum Qualifications

Education: PhD in Machine Learning, Computer Science, Computational Biology, Bioinformatics, or a related quantitative field. 

The level will be based on relevant experience and track record of technical and people leadership gained within a biotech or AI driven life sciences environment. Typically:

• Director: PhD + 10+ years experience with a proven track record, with a minimum of  4–5 years of experience, in people management.
• Senior Director: PhD +14+ years experience, with 7–8+ years of people/team leadership, and a demonstrable broad background driving multiple programs through multi disciplinary teams.

The hiring range for Redwood City, CA:

• Director: $265,400 - $340,200
• Senior Director $347,700- $445,800

The hiring range for San Diego, CA:

• Director: $261,500- $335,300
• Senior Director $305,800- $392,100

Exact compensation may vary based on skills, experience, and location.

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