Associate Scientist/Scientist I, Protein Science Developability
Lila Sciences · Cambridge, MA USA · One Charles Park, Cambridge, MA
CHECKED 15H AGO
Bio & Science AIonsiteassociate$88k–$144k
At a glance
Highlights
- Design high-throughput protein purification workflows for diverse protein classes.
- Integrate protein workflows into automated workcells with AI and engineering teams.
- Advance Lila's Scientific Superintelligence platform to accelerate discovery.
What they offer
- Competitive base compensation with bonus potential
- Generous 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
- Commuter benefits including bike share
- Company-subsidized lunch program
Ideal candidate
A meticulous, collaborative protein scientist who thrives in fast-paced, automated labs and cares deeply about data quality, reproducibility, and accelerating discovery.
Requirements
- MS in Biochemistry, Biophysics, Bioengineering, Molecular Biology or related field with 4+ years experience, or PhD with 0-2 years postdoc or industry experience
- Experience operating AKTA chromatography systems across affinity, SEC, HIC, IEX with workflow development and troubleshooting
- Hands-on LC-MS for protein characterization including intact mass, peptide mapping, PTM and glycosylation analysis
- Familiarity with bioassay development and data analysis for ELISA, AlphaLISA, SPR/BLI and functional assays
- Strong lab data analysis, digital recordkeeping in Benchling and collaborative workflows
- Outstanding analytical and problem-solving skills with attention to data quality and reproducibility
- Effective communication and eagerness to collaborate in fast-paced cross-functional team
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