USASenior / Principal ML Scientist, Foundation Models for Life Sciences
3 мес. назад
USALead
machine learningscikit-learnpytorchtensorflowdata analysis
Lead research and development of large-scale foundation models for life sciences, focusing on generative AI applied to biological data.
Будет плюсом
- Experience in computational protein design, particularly antibody and nanobody engineering
- Experience designing biological sequences or molecular structures with demonstrated wet-lab validation
- Contributions to open-source ML tools, frameworks, or benchmark datasets for scientific applications
- Experience with agentic frameworks or active learning loops in scientific contexts
- High-impact publications or open‑source contributions in AI for Science in relevant venues (NeurIPS, ICML, ICLR, AAAAI, Nature Methods, Nature Biotechnology, or equivalent)
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Условия
- We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.
- U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.
- International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.
Другое
- Lila is building a platform where AI and automation co-evolve to solve the hardest problems in medicine. Within Life Science AI (LSAI), the Foundation Models team researches and develops large-scale generative models and reasoning frameworks that power automated scientific discovery across Lila's life science domains.
- We are seeking a Principal or Senior Principal Scientist to join this team as a core contributor. You will define and drive research at the intersection of state-of-the-art machine learning and life science data, spanning biological sequences, molecular structures, and multimodal experimental data. As part of a dynamic team, you will design and implement foundational models end to end, from problem formulation and architecture through training at scale, evaluation, and integration into Lila's closed-loop discovery engine.
- This is a high-impact IC role for someone who operates at the frontier of generative AI applied to biology. You will shape the technical agenda for foundation model research, collaborate closely with experimental scientists to close the computational-experimental loop, and represent Lila's work to the broader scientific community.
- Drive research on foundation models for life science applications, including but not limited to biological sequence design, structure prediction, and multimodal scientific reasoning
- Design, train, and evaluate large-scale generative models on biological and chemical data, integrating domain-specific constraints and priors
- Contribute to the end-to-end ML process within Lila's "Lab-in-the-Loop" lifecycle: steer data generation strategy, build pipeline models, and design feedback loops where experimental results improve model performance
- Translate complex biological questions into well-defined ML problems and interpret model outputs in collaboration with wet-lab scientists and computational biologists
- Advance research standards and methodology within the foundation models program, contributing insights that influence approaches across adjacent teams
- Represent Lila's foundation model research externally through publications at premier venues, conference presentations, and community engagement
- PhD in Computer Science, Machine Learning, Computational Biology, or a related quantitative field
- Multiple high-impact first-author or senior-author publications at premier venues (NeurIPS, ICML, ICLR, Nature Methods, Nature Biotechnology, or equivalent)
- Deep expertise in large-scale generative model architectures and training, with hands-on experience training models on distributed infrastructure
- Demonstrated ability to formulate and drive research programs independently, from problem definition through publication and deployment
- Fluency across ML and at least one life science domain (molecular biology, genomics, protein engineering, nucleic acid design, or related), with experience designing computational experiments grounded in biological reality
- Strong track record of cross-functional collaboration with experimental scientists, translating between ML and biology
- Expertise in ML frameworks (PyTorch, JAX, or TensorFlow) and experience with large-scale distributed training infrastructure (AWS, GCP, or on-prem clusters)
- Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.
- LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at
- Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.
- Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
- Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy .
- Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.