Lila Sciences
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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 applying AI to every aspect of the scientific method to solve humankind’s greatest challenges in health, climate, and sustainability. 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. Your Impact at Lila
We’re hiring a
(Senior) Scientist, Nucleic Acid Delivery
to lead development of next-generation platforms for targeted delivery of nucleic acid–based therapeutics, including lipid nanoparticles and alternative gene delivery systems. The role spans developing novel chemistries, targeting strategies, and formulations; standing up high-throughput, automated screens; and building novel characterization methods that explain and predict performance. You’ll partner with chemistry, biology, automation/robotics, and AI teams and leverage both internal teams and external CROs to turn design–build–test–learn into a closed loop that continuously improves therapeutics discovery, development, and delivery. What You’ll Be Building
Key Responsibilities
Design modality-spanning libraries of delivery systems (LNPs and alternatives), exploring novel chemistries, architectures, and targeting strategies (antibodies/VHHs/peptides/glycans; tunable linker chemistries). Implement state-of-the-art and develop next-generation characterization methods to evaluate formulation and delivery performance. Establish in-vitro assays and collaborate with external partners to design and execute in-vivo studies. Closed-Loop Experimentation and Execution: partner with engineering and automation to design and operate platforms for automated, high-throughput experimentation and data-rich workflows. Collaborate with the AI team to run iterative experiments in real time, enabling fast optimization and discovery cycles. Collaborate, Lead & communicate: work with chemists, material scientists, engineers, 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 organization. What You’ll Need to Succeed
Ph.D. in Chemical/Biomedical Engineering, Chemistry, Pharmaceutical Sciences, Biochemistry, or related field (or M.S./B.S. with 5–8+ years relevant industry experience). Deep expertise in nucleic-acid therapeutics, targeted delivery platforms, and biophysical/bioanalytical assays. Experience building and implementing in vitro assays and integrating analytical instruments into automated or modular experimentation platforms. Experience engaging with external partners such as CROs in designing and shepherding in vivo studies, including mouse and NHPs. Strong working knowledge of automation/HTS and experimental design/statistics including design-of-experiments and Bayesian optimization. Proficiency in Python or other scripting languages for data analysis. Clear, concise documentation and communication; bias toward hypothesis-driven, quantitative decision-making. Bonus Points
Targeted nanoparticle experience (antibody/ligand decoration, linker chemistry) and affinity analytics (SPR/BLI). Familiarity with GMP considerations for nanoparticle manufacturing. Familiarity with mRNA chemistry (base/cap/poly(A) engineering) and how cargo design interacts with LNP performance. How We’ll Measure Success (6–12 months)
Creation of novel targeted delivery technologies with verified improvements in potency/selectivity and clear mechanistic rationales. Deployment of new characterization methods that increase predictive signal while reducing assay burden. Demonstrated closed-loop acceleration: higher hit rates, shorter iteration cycles, and prospective wins from model-guided designs. High-quality datasets and insights that unlock new design rules and inform platform roadmaps. 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. 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.
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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 to solve humankind’s greatest challenges in health, climate, and sustainability. 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. Your Impact at Lila
We’re hiring a
(Senior) Scientist, Nucleic Acid Delivery
to lead development of next-generation platforms for targeted delivery of nucleic acid–based therapeutics, including lipid nanoparticles and alternative gene delivery systems. The role spans developing novel chemistries, targeting strategies, and formulations; standing up high-throughput, automated screens; and building novel characterization methods that explain and predict performance. You’ll partner with chemistry, biology, automation/robotics, and AI teams and leverage both internal teams and external CROs to turn design–build–test–learn into a closed loop that continuously improves therapeutics discovery, development, and delivery. What You’ll Be Building
Key Responsibilities
Design modality-spanning libraries of delivery systems (LNPs and alternatives), exploring novel chemistries, architectures, and targeting strategies (antibodies/VHHs/peptides/glycans; tunable linker chemistries). Implement state-of-the-art and develop next-generation characterization methods to evaluate formulation and delivery performance. Establish in-vitro assays and collaborate with external partners to design and execute in-vivo studies. Closed-Loop Experimentation and Execution: partner with engineering and automation to design and operate platforms for automated, high-throughput experimentation and data-rich workflows. Collaborate with the AI team to run iterative experiments in real time, enabling fast optimization and discovery cycles. Collaborate, Lead & communicate: work with chemists, material scientists, engineers, 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 organization. What You’ll Need to Succeed
Ph.D. in Chemical/Biomedical Engineering, Chemistry, Pharmaceutical Sciences, Biochemistry, or related field (or M.S./B.S. with 5–8+ years relevant industry experience). Deep expertise in nucleic-acid therapeutics, targeted delivery platforms, and biophysical/bioanalytical assays. Experience building and implementing in vitro assays and integrating analytical instruments into automated or modular experimentation platforms. Experience engaging with external partners such as CROs in designing and shepherding in vivo studies, including mouse and NHPs. Strong working knowledge of automation/HTS and experimental design/statistics including design-of-experiments and Bayesian optimization. Proficiency in Python or other scripting languages for data analysis. Clear, concise documentation and communication; bias toward hypothesis-driven, quantitative decision-making. Bonus Points
Targeted nanoparticle experience (antibody/ligand decoration, linker chemistry) and affinity analytics (SPR/BLI). Familiarity with GMP considerations for nanoparticle manufacturing. Familiarity with mRNA chemistry (base/cap/poly(A) engineering) and how cargo design interacts with LNP performance. How We’ll Measure Success (6–12 months)
Creation of novel targeted delivery technologies with verified improvements in potency/selectivity and clear mechanistic rationales. Deployment of new characterization methods that increase predictive signal while reducing assay burden. Demonstrated closed-loop acceleration: higher hit rates, shorter iteration cycles, and prospective wins from model-guided designs. High-quality datasets and insights that unlock new design rules and inform platform roadmaps. 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. 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.
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