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Head of Machine Learning, Cell Biology

insitro

insitro

Software Engineering, Data Science
South San Francisco, CA, USA
USD 315k-360k / year + Equity
Posted on Aug 22, 2025

The Opportunity

insitro's mission is to use AI and machine learning to develop medicines for patients with diseases that have little to no effective treatment. As a field, drug discovery and development has faced a decades-long decline in productivity characterized by high failure rates in the clinic, primarily due to a lack of understanding the underlying biology of disease. This is despite billions spent to build models of biology, whether in the lab or animal models, to predict clinical success. Ultimately, we need better predictive models.

With this vision, insitro has built a target and biology discovery engine, which combines high throughput, multimodal cellular phenotyping and perturbation data generation with novel machine learning and AI methods. As Head of CellML, you will lead the team of ML scientists and engineers that will develop methods capable of generating biology insights from multiple data modalities collected at scale, spanning live and fixed microscopy imaging, and diverse omics assays (scRNA, proteomics, spatial). You will also partner with our laboratory leadership to co-develop the next generation of high-scale perturbation cellular assays ranging from Optical Pooled Screening, live-cell staining imputation, Perturb-seq, and more. Finally, you will collaborate with our therapeutic area leaders to design the right experiments and analyze the data so as to advance our therapeutic pipeline.

You will be joining a well funded AI biotech that has established a pipeline of therapeutic candidates and is expanding into a growing array of disease areas. We are looking for leaders who can develop a culture combining science, machine learning, and engineering. This role will report to our Head of Compute and is a hybrid role, requiring you to be in our South San Francisco headquarters at least three days per week.

Responsibilities

  • Work collaboratively with our Drug Discovery leaders on the strategy for deployment of advanced ML to empower target discovery and biological insights, driving the design of experiments that generate data that enables the use of advanced ML methods
  • Lead and grow a team of outstanding machine learning scientists
  • Onboard and develop ML and bioinformatic methods for interpreting complex multi-modal perturbation data. Relevant topics include representation learning, contrastive approaches to isolating salient features, disentanglement approaches for interpretability and statistical power, multi-modal embedding, uncertainty modeling, and more.
  • Lead yearly and quarterly planning, set impactful goals, and align with cross-functional stakeholders
  • Engineer robust, reusable platform components in partnership with the software engineering team
  • Work with our platform biology and automation teams to advance our platform capabilities, including both: (i) the development of new wet lab capabilities and (ii) the advancement of new ML methods, including by generation of data explicitly designed for training ML models
  • Collaborate with the corporate development and strategy teams to drive discussions with potential external partners and maximize the value created by our platform technologies

About You

  • Technical skills:
    • Ph.D. in computer science, mathematics, biology, bioinformatics, or a related discipline, or equivalent practical experience
    • 12+ years of real-world experience in applying AI/ML methods to cellular data
    • Demonstrated in-depth knowledge in the foundations and practice of modern machine learning, including deep learning
    • Experience with both imaging and omics modalities
    • Experience in the use of cellular data in the context of drug discovery efforts a nice to have
    • Peer reviewed publications in high-quality conferences or journals
  • Leadership experience:
    • Experience in people management and leadership, including building and developing team members based on the strategic needs of the company
    • Demonstrated ability to collaborate effectively with life science colleagues to form research and therapeutic pipeline execution roadmaps.
    • Demonstrated ability to lead a team of scientists and engineers to plan, execute and deliver a full machine learning solution for challenging, real-world problems: sourcing and qualifying training data; designing and implementing machine learning models; testing & benchmarking; shipping stable, robust, high-performance code.
    • Passion for providing better medicine to patients in need

Compensation & Benefits at insitro

Our target starting salary for successful US-based applicants for this role is $315,000 - $360,000. To determine starting pay, we consider multiple job-related factors including a candidate's skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data.

This role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan, subject to the terms of those plans and associated policies.

In addition, insitro also provides our employees:

  • 401(k) plan with employer matching for contributions
  • Excellent medical, dental, and vision coverage as well as mental health and well-being support
  • Open, flexible vacation policy
  • Paid parental leave of at least 16 weeks to support parents who give birth, and 10 weeks for a new parent (inclusive of birth, adoption, fostering, etc)
  • Quarterly budget for books and online courses for self-development
  • Support to attend professional conferences that are meaningful to your career growth and role's responsibilities
  • New hire stipend for home office setup
  • Monthly cell phone & internet stipend
  • Access to free onsite baristas and cafe with daily lunch and breakfast for employees who are either onsite or hybrid
  • Access to free onsite fitness center for employees who are either onsite or hybrid
  • Access to a free commuter bus and ferry network that provides transport to and from our South San Francisco HQ from locations all around the Bay Area

insitro is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

We believe diversity, equity, and inclusion need to be at the foundation of our culture. We work hard to bring together diverse teams–grounded in a wide range of expertise and life experiences–and work even harder to ensure those teams thrive in inclusive, growth-oriented environments supported by equitable company and team practices. All candidates can expect equitable treatment, respect, and fairness throughout the interview process.

#LI-Hybrid

Please be aware of recruitment scams: we never request payments, all recruitment communications are from @insitro.com, and if in doubt, contact us at info@insitro.com.

About insitro
insitro is a drug discovery and development company using machine learning (ML) and data at scale to decode biology for transformative medicines. At the core of insitro’s approach is the convergence of in-house generated multi-modal cellular data and high-content phenotypic human cohort data. We rely on these data to develop ML-driven, predictive disease models that uncover underlying biologic state and elucidate critical drivers of disease. These powerful models rely on extensive biological and computational infrastructure and allow insitro to advance novel targets and patient biomarkers, design therapeutics and inform clinical strategy. insitro is advancing a wholly owned and partnered pipeline of insights and therapeutics in neuroscience and metabolism. Since launching in 2018, insitro has raised over $700 million from top tech, biotech and crossover investors, and from collaborations with pharmaceutical partners. For more information on insitro, please visit www.insitro.com.