Senior/Principal Scientist, Small Molecule Therapeutics

Your Impact at LILA The Senior/Principal Scientist, Small Molecule Therapeutics will lead early hit identification efforts, leveraging their expertise in DNA-encoded libraries (DEL) and complementary screening technologies to discover and validate novel chemical matter. This role will partner cross-functionally with Lila’s Chemistry, Computational, and Automation teams to develop and scale a best-in-class small molecule screening platform. The Senior/Principal Scientist will also drive the progression of hits through optimized biochemical and biophysical assay cascades, while identifying and securing fit-for-purpose protein sources to enable robust characterization and follow-up. What You'll Be Building Build and continuously improve DNA-encoded library (DEL) screening capabilities, tightly integrated with Lila’s AI-enabled chemistry design engine and automated/robotic synthesis platform. Design and execute DEL screening campaigns, including selection strategy, experimental execution, data interpretation, and translation into robust hit validation and hit-to-lead workflows. Develop, optimize, and run fit-for-purpose biochemical and biophysical assays to validate and characterize hits emerging from Lila’s screening platform. Evaluate, implement, and operationalize complementary screening modalities (e.g., fragment, affinity-based, functional, and other relevant approaches) to expand hit-finding coverage and diversify chemotypes. Establish and manage collaborations (internal and external) to secure high-quality protein supply suitable for high-throughput screening and assay development. Define, produce, and triage optimal protein constructs (including construct design and quality criteria) to enable reliable screening performance and confident downstream hit validation. What You'll Need to Succeed Education & experience: PhD in Biology, Chemical Biology, Biochemistry, or a related field with 6–8 years of relevant drug discovery experience; or MS/BS with 10+ years of industry experience in small molecule discovery, screening, and hit finding. DEL expertise: demonstrated success designing, executing, and delivering impactful DNA-encoded library (DEL) screening campaigns, from selection strategy through validated hits that enable downstream chemistry. Hit identification breadth: strong working knowledge of complementary screening approaches (e.g., fragment-based, affinity-based, functional/phenotypic, and other relevant modalities) to diversify hit sources and chemotypes. Assay development & validation: experience developing and optimizing biochemical and biophysical assays to triage, validate, and characterize screening hits, including assay quality metrics and troubleshooting. Biophysics proficiency: hands-on experience with affinity/biophysics methods used in hit confirmation and ranking (e.g., SPR, BLI, DSF, ITC, MST, or comparable techniques), with the ability to interpret data critically. Automation-forward mindset: experience operating in automation- and robotics-enabled labs, including liquid handling integration, assay automation, and designing scalable, reproducible experimental workflows. Protein partnership: proven ability to collaborate closely with protein science collaborators to enable screening, spanning construct strategy, expression system selection, purification requirements, and quality criteria for assay readiness. Comprehensive hit-to-lead understanding: clear understanding of the full hit identification and validation funnel, including orthogonal confirmation, selectivity/counterscreens, artifact mitigation, and translation into hit-to-lead-enabling data packages. Mechanism-driven assay design: ability to establish and optimize activity assays to prioritize binding hits, probe mechanism of action, and guide follow-up experiments and medicinal chemistry decisions. Cross-functional effectiveness: strong record of operating in highly interdisciplinary environments across chemistry, biology, automation, and computational teams, with excellent scientific communication and stakeholder alignment skills. Bonus Points For Deep expertise in large-scale screening approaches, including DNA-encoded libraries (DEL), fragment-based screening, and other contemporary small molecule discovery technologies. Strong command of screening data analysis, interpretation, and stewardship of large experimental datasets (including clear data QC, hit calling, and prioritization frameworks). Hands-on experience across multiple biophysical modalities (e.g., SPR, BLI, DSF, MST, ITC, MS-based methods) and the ability to select fit-for-purpose methods for confirmation and ranking. Extensive understanding of biochemical activity assays, including development, optimization, and interpretation across common readouts (luminescent, colorimetric, fluorometric, and label-free formats). Experience designing, producing, and evaluating protein constructs that enable robust, scalable high-throughput screening and downstream validation. Familiarity operating in AI-enabled drug discovery environments and/or integrating machine learning outputs into experimental design, prioritization, and iterative learning cycles. Experience building screening capabilities end-to-end, including instrumentation evaluation/selection, workflow design, and lab automation implementation. Ability to thrive in a fast-paced, highly innovative environment. Excellent communication skills, with the ability to synthesize and explain complex datasets to diverse audiences across chemistry, biology, automation, and computational teams. Compensation 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. Expected Base Salary Range

$148,000—$208,000 USD

About LILA 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. 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 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.