Director / Senior Director, Machine Learning for Biology

Our mission is to restore cell health and resilience through cell rejuvenation to reverse disease, injury, and the disabilities that can occur throughout life. altoslabs.com

About Us

Altos Labs has been named one of the Top 3 Biotech Companies and ranked for the second year on the Forbes 2026 Best Startups in America list. At Altos, exceptional scientists and industry leaders from around the world work together to advance a shared mission. Our intentional focus is on Belonging, so that all employees know they are valued for their unique perspectives. We are all accountable for sustaining a diverse and inclusive environment.

Responsibilities

• Partner with the rest of the IoC Leadership Team to co-define and steer Altos’ core technical agenda, strategically identifying and prioritizing the most critical biological questions where machine learning can drive breakthroughs in cell rejuvenation and resilience, ensuring ML investments are deployed against highest-impact scientific frontiers rather than pure technical advancement.
• Build and maintain strong partnerships with key stakeholders and leaders across different functions at Altos.
• Lead a team of ML Scientists and Engineers, while staying hands-on enough to provide direct technical guidance across IoC's highest-impact ML programs.
• Provide technical and strategic guidance and advice on ML project design and de-risking across multiple teams, drawing on deep intuition for what drives success or failure in ML-for-biology projects, backed by established experience.
• Provide sustained technical mentorship and strategic guidance, supporting the professional development and growth of the team while proactively growing IoC's ML bench through training, coaching, and active recruitment of outstanding talent.
• Lead effectively in a matrixed environment, influencing technical direction on projects and teams outside your direct reporting line, and aligning priorities across IoC's ML programs even where you don't hold reporting authority.

Requirements

• Deep knowledge and understanding of common and state-of-the-art AI/ML methods and innovations and large-scale training procedures, applied to biological data modalities (e.g., single-cell, perturbation-response, spatial, or sequence data).
• Broad expertise and mastery across various AI/ML domains, specifically:
  • Reasoning and open-ended learning framework design for scientific hypothesis generation and evaluation;
  • Large-scale pretraining, fine-tuning, and post-training of foundation models, including RL, distillations, finetuning, and strategies to reduce hallucination and align model objectives with scientific discovery;
  • Model architectures that span multimodal generative and predictive modeling (normalizing flows, diffusion models, LLMs) for out-of-distribution generalization in biological systems;
  • Hybrid modeling approaches — model identifiability, robustness, and regularized/interpretable methods such as anchor or energy-based models — for biological tasks, including target identification; semantic-based dynamic inference, virtual cell and world model paradigms.
• A strong track record of leading innovative biological ML projects to success, while foreseeing and mitigating ML project failure modes at scale.
• Ability to think strategically and optimize for the long term while acting and delivering with pace.
• Ability to contribute to a culture of continuous learning and technical innovation, ensuring a rigorous balance between creative exploration and strategic resource allocation and priorities.
• Stay current with scientific and data science advancements, integrating relevant knowledge into computational biology.
• Intellectually curious with a strong pulse on the computational landscape, and ability to decipher and prioritize AI trends from hype to maintain a competitive edge.

Qualifications

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.

• 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 multidisciplinary teams.

Pay

• Redwood City, CA
  • Director: $297,400 - $381,300
  • Senior Director: $366,800 - $470,200
• San Diego, CA
  • Director: $273,900 - $351,100
  • Senior Director: $337,700 - $432,900

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