Director, AI for Protein Engineering
About The Position
Lila is embarking on a transformative mission to redefine the future of medicine by combining automated large-scale data generation with scientific superintelligence. We are seeking a visionary leader to serve as the Director, AI for protein engineering. In this pivotal role, you will build and lead a world-class team of computational and ML scientists from the ground up, dedicated to computational design of peptides, antibodies and enzymes. You will bridge the gap between cutting-edge generative AI and life-saving medicine, overseeing the design strategy for Lila’s biomolecule-based portfolio.
Requirements
- Proven Design Impact: The primary requirement is a track record of successful design of wet-lab validated biomolecules through AI.
- Education: PhD with a focus on computation, specifically in Computational Structural Biology or Computer Science, preferably with AI-driven drug discovery focus
- Technical Track Record: A portfolio of peer-reviewed publications or patents. We are specifically looking for first-author contributions in premier venues:
- ML Focus: ICLR, ICML, or NeurIPS (Full track).
- Biology/Nature Focus: Nature Methods, Nature Biotechnology, Nature Structural & Molecular Biology, Nature, Science, or Cell.
- Leadership: Demonstrated experience building and leading multidisciplinary teams and managing complex research portfolios in a biotech or pharmaceutical environment.
- Communication: Exceptional skills in translating high-dimensional ML concepts (e.g., latent space representations, folding dynamics) for biological scientists and presenting strategic visions to executive stakeholders.
- Location: This role is based in San Francisco, CA or Boston, MA, with a strong preference for candidates located in or willing to relocate to San Francisco.
Responsibilities
- Team Leadership: Recruit, mentor, and scale a high-performing team of ML researchers and computational biologists. Foster a culture of "bilingual" excellence that thrives at the intersection of AI and biology.
- Scientific Strategy: Drive the research and implementation of generative ML models for biomolecule design, including: diffusion models, protein language models (pLMs), and structure-conditioned sequence generation.
- Portfolio Management: Supervise the development of our protein therapeutic portfolio, ensuring projects meet key milestones, from initial in silico design to lead optimization and developability assessment.
- Cross-Functional Synergy: Act as the primary bridge to our Life Science Experimental Research team. You will ensure computational designs are optimized for "wet-lab" validation and design the active learning feedback loops where experimental data (e.g., binding affinity, stability) improves our generative models.
- Product Integration: Partner with Life Science Product Management to align the technical roadmap with Lila’s commercial goals and therapeutic priorities.
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What This Job Offers
Job Type
Full-time
Career Level
Director
Education Level
Ph.D. or professional degree
