Lila Sciences
Platform Scientist, Soft Materials
Cambridge, MA USA · Full-time
Sponsorship not specified$108k-$150kDetected 16 days ago
PythonC++Machine LearningData AnalysisA/B TestingRecruitingCommunication
About the role
- In this role, you will work at the forefront of scientific ideation-partnering with a broad range of chemistry, materials, and AI teams to define new approaches to formulation, structure-property relationships, and performance evaluation.
- You will translate these concepts into scalable experimental workflows, custom apparatus, and software-enabled systems for autonomous research.
- Your final offer will reflect your background, expertise, and expected impact.
Responsibilities
- Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges.
- Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.
- Lead conceptual development of characterization and performance workflows leveraging techniques such as SAXS, SANS, rheology, and formulation performance assays
- Design, prototype, and validate custom apparatus, experimental methods, and software tools to realize these concepts
- Develop and refine workflows that connect structure, dynamics, and performance across multiple length and time scales
Requirements
- Experience with lab automation, high-throughput experimentation, or instrument control software
Compensation
- We offer competitive base compensation with bonus potential and generous early-stage equity.
- USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.
- Expected Base Salary Range
- $108,000 - $150,000 USD
Visa & Work Authorization
- al employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status
Apply directly at Lila Sciences →Create a free account for alerts like thisView Lila Sciences immigration profile
This listing is sourced directly from Lila Sciences's careers page and normalized into a canonical job model.