Director, Machine Learning, Virtual Cell Initiative

Arc Institute • Palo Alto, CA

6h • Onsite

About The Position

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.

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.

Nice To Haves

• Passionate about machine learning, ideally with experience or strong interest in biology and single-cell genomics.
• Develop highly innovative and accurate biology-inspired multimodal machine learning models.
• Excited about collaborating with a multidisciplinary team of computational and experimental biologists at Arc.
• Strong communicator, capable of translating complex technical concepts at the intersection of machine learning and biology.
• Continuous learner.
• Interested in recruiting and managing your own group of scientists and engineers as well as mentoring and training for other scientists.

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.
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree