Scientist I, Expression Platform, Mammalian Cells

Lila Sciences
Cambridge, MA USAPosted 26 March 2026

Tech Stack

Job Description

Your Impact at Lila Role will lead development and validation of novel mammalian cell based pooled assays. The role will span proof of concept to automated screens to generate highly multiplexed and high dimensional datasets. The role will partner across cell biology, protein design and nucleic acid teams to support biologic development programs with the rapid determination of binding, stability, function, and immunogenicity of a variety of biologics. What You'll Be Building Build next-generation mammalian display based binding, stability, function, and immunogenicity assays. Implement state-of-the art multiomic, single cell and in situ sequencing workflows to create novel highly multiplexed assays. Partner with protein design, nucleic acid, protein and automation teams to apply these workflows to the development of biologics. Closed-Loop Experimentation and Execution: partner closely with engineering and automation to design and exercise platforms for automated, high-throughput experimentation and data-rich workflows. Collaborate with AI team to run iterative experiments in real time, enabling fast optimization and discovery cycles. Collaborate, Lead communicate: Work with cell biologists, synthetic biologists, automation engineers, protein design scientists and data scientists to document systems, share insights, and refine best practices in autonomous science. Mentor junior scientists, align milestones with internal/external collaborators, contribute to IP and publications, and present findings across the org. What You’ll Need to Succeed Ph.D. in Chemical/Biomedical Engineering, Biochemistry, Pharmaceutical Sciences, Immunology, or related field (or M.S./B.S. with 5–8+ years relevant industry experience). Expertise with the development and/or application of mammalian display or similar pooled mammalian (perturb-seq, MPRA, etc.) systems Expertise with designing, executing and analyzing single cell, in situ or multiomic sequencing based experiments Experience designing novel single cell, in situ or multiomic sequencing based techniques Experience designing, executing and analyzing flow cytometry and sorting based experiments Experience creating highly complex libraries of defined sequences in mammalian cells Experience designing, executing and analyzing NGS based experiments Bonus Points For Experience with antibody or cell therapy development Imaging experience Experience with optical pooled screening or image-based cell sorting Experience with encapsulation/droplet/bead/microwell based antibody or cell screening About Lila Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science.  We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method.  We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at www.lila.ai If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, we encourage you to apply. We’re All In 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 . A Note to Agencies 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 a ... (truncated, view full listing at source)
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