Director, Machine Learning, Virtual Cell Initiative

About the role

We are searching for an innovative scientific leader experienced in building predictive models based on single-cell genomic data. The chosen candidate will spearhead the development and application of advanced machine learning models tailored for perturbative gene expression modeling, in the context of Arc’s virtual cell initiative.

Responsibilities

• Lead/build a team of 6 ML research scientists and engineers augmented with undergrad/masters/PhD students to contribute to the development of a state-of-the-art foundation model and agentic framework for understanding how cells respond to perturbations.
• Work in an active learning loop with Arc’s wet lab scientists to shape the world's largest and most diverse set of single cell training data across many cell contexts.
• Collaborate closely with other research groups to integrate genomics, functional track, and omics data more broadly beyond scRNA-seq data and Perturb-seq.
• Stay up to date on the latest in frontier ML research and pioneer new architectures and approaches.
• The ultimate goal is to build a high utility virtual cell model for use by biologists worldwide. We publish our breakthroughs to widely accelerate scientific progress and partner with some of the biggest names in AI.
• Commit to a collaborative and inclusive team environment, sharing expertise and mentoring others.
• Attract the very best talent in the world to support VCI initiative goals

Requirements

• PhD in Computational Biology, Bioinformatics, Machine Learning, or a related field.
• Minimum of 5 years of experience working in/with machine learning, well versed in frameworks such as Pytorch, TensorFlow, JAX, etc.
• Proven experience leading research teams in a fast paced, multi-disciplinary environment.
• Experience with or strong interest in biology with ability to communicate and collaborate successfully with biologists and pure ML engineers.
• Excellent communication skills, both written and verbal, with a strong track record of presentations and publications.

Pay

The base salary range for this position is $380,000-$420,000. These amounts reflect the range of base salary that the Institute reasonably would expect to pay a new hire or internal candidate for this position. The actual base compensation paid to any individual for this position may vary depending on factors such as experience, market conditions, education/training, skill level, and whether the compensation is internally equitable, and does not include bonuses, commissions, differential pay, other forms of compensation, or benefits. This position is also eligible to receive an annual discretionary bonus, with the amount dependent on individual and institute performance factors.