Principal Scientist, Library Technologies Job at Lila Sciences in Cambridge

Overview

Principal Scientist, Library Technologies

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 applying AI to every aspect of the scientific method. Learn more at www.lila.ai.

At Lila, we value an inclusive mindset and diverse perspectives. Our teams thrive in unstructured, creative environments where all voices are heard, and where experience comes in many forms and skills are transferable.

If this sounds like a role you’d enjoy, please apply.

Responsibilities

• Design and execute strategies for library technology platforms, constructing and screening large-scale genetic libraries using cDNA, yeast surface, and mammalian display methods. Design, develop, and optimize display systems for selection of binding proteins, functional antibodies, and other therapeutic candidates.
• Lead and optimize strategies for library generation, display expression, and selection reagents for difficult targets such as GPCRs.
• Collaborate with machine learning, protein engineering, cell engineering, and informatics teams to enable hit selection and sequence-to-function model development.
• Partner with automation teams to build scalable, reproducible workflows across liquid handlers, FACS, and plate-based screening platforms.
• Mentor junior scientists, foster a culture of innovation and rigor, contribute to company-wide scientific strategy planning, and drive cross-functional project design with scientific and technical leadership.

What You’ll Need to Succeed

• Ph.D. in Molecular Biology, Protein Engineering, Biochemistry, Synthetic Biology, or a related discipline with 8+ years of industry or postdoctoral experience.
• Proven track record of developing and applying display technologies (e.g., cDNA display, yeast display, mammalian cell display) to protein or antibody discovery.
• Strong experience in library design, construction, FACS-based selection, NGS-based sequencing methods, and functional screening is highly desirable.
• Familiarity with automation tools (e.g., liquid handlers, FACS sorters) and data-driven optimization of selection campaigns.
• Experience working in cross-functional environments with machine learning, biology, automation, and informatics.
• Mentoring experience and a demonstrated ability to grow high-performing scientific teams.
• Excellent communication, collaboration, and organizational skills.

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.

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 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.