Senior/Principal Scientist, Small Molecule Therapeutics
Lila Sciences · Cambridge, MA USA · Alewife, Cambridge, MA
CHECKED 13H AGO
Bio & Science AIonsitesenior$148k–$208k
At a glance
Highlights
- Lead early hit identification to discover novel chemical matter.
- Build AI-enabled small molecule screening platform with automation.
- Drive hits from validation through hit-to-lead workflows.
What they offer
- Competitive base compensation with bonus potential and early-stage equity
- Medical, dental and vision coverage
- Employer-paid life and disability insurance
- Flexible time off with company-wide holidays
- Paid parental leave
- Educational assistance program
- Company-subsidized lunch program
Ideal candidate
Drug discovery scientist with 6+ years in small-molecule hit finding who thrives in fast-paced, automation-driven teams and loves building screening platforms that power AI-guided chemistry.
Requirements
- PhD in biology or related field with 6-8 years drug discovery experience or MS/BS with 10+ years
- Proven success designing and executing DNA-encoded library screening campaigns to validated hits
- Working knowledge of complementary hit-finding modalities including fragment, affinity and functional approaches
- Experience developing and optimizing biochemical and biophysical assays for hit validation
- Hands-on affinity characterization using methods such as SPR, BLI, DSF, ITC or MST
- Experience in automation-enabled labs with liquid handling and scalable workflows
- Ability to partner on protein construct strategy, expression and quality criteria for screening
- Understanding of hit-to-lead funnel including counterscreens, artifact mitigation and data packages
- Track record collaborating across chemistry, biology, automation and computational teams
Lab profile
About Lila Sciences
Building an autonomous science platform where AI, automation, and biology co-evolve for medicine and materials.
What they build
- Autonomous Science Platform
- AI-designed biologics validated in wet-lab
- Electro-optic materials and photonic devices
Known for
- Large-scale automated data generation
- High-throughput protein purification and analytics
- Protein design and BioML modeling
- Robotic orchestration and lab simulation