Senior/principal Scientist, Small Molecule Therapeutics

Lila Sciences Lila Sciences · AI Frontier · Alewife, Cambridge, MA · Autonomous Science Platform

Lead early hit identification efforts in small molecule therapeutics by leveraging expertise in DNA-encoded libraries (DEL) and complementary screening technologies to discover and validate novel chemical matter. Partner cross-functionally with Chemistry, Computational, and Automation teams to develop and scale a small molecule screening platform. Drive hit progression through assay cascades and secure protein sources for characterization.

What you'd actually do

  1. 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.
  2. Design and execute DEL screening campaigns, including selection strategy, experimental execution, data interpretation, and translation into robust hit validation and hit-to-lead workflows.
  3. Develop, optimize, and run fit-for-purpose biochemical and biophysical assays to validate and characterize hits emerging from Lila’s screening platform.
  4. 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.
  5. Establish and manage collaborations (internal and external) to secure high-quality protein supply suitable for high-throughput screening and assay development.

Skills

Required

  • 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.
  • demonstrated success designing, executing, and delivering impactful DNA-encoded library (DEL) screening campaigns, from selection strategy through validated hits that enable downstream chemistry.
  • 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.
  • experience developing and optimizing biochemical and biophysical assays to triage, validate, and characterize screening hits, including assay quality metrics and troubleshooting.
  • 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.
  • experience operating in automation- and robotics-enabled labs, including liquid handling integration, assay automation, and designing scalable, reproducible experimental workflows.
  • 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.
  • 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.
  • ability to establish and optimize activity assays to prioritize binding hits, probe mechanism of action, and guide follow-up experiments and medicinal chemistry decisions.
  • strong record of operating in highly interdisciplinary environments across chemistry, biology, automation, and computational teams, with excellent scientific communication and stakeholder alignment skills.

Nice to have

  • 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.

What the JD emphasized

  • DEL screening campaigns
  • biochemical and biophysical assays
  • protein constructs