Lila: Senior / Scientist, Nucleic Acid Delivery

🚀 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.

🌟 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 will span 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 team 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 are 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 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 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 org.

🧰 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 developing 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 For

• 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 (e.g., better correlation to in vivo outcomes) 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.