Staff / Principal Automated Systems Engineer
Lila Sciences · Cambridge, MA USA · One Charles Park, Cambridge, MA
CHECKED 15H AGO
Bio & Science AIonsitestaff$163k–$228k
At a glance
Highlights
- Build scalable high-throughput automated workcells for lab workflows.
- Develop automation for synthesis and characterization of advanced materials.
- Translate scientific intent into reliable real-world automated systems.
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
- Commuter benefits including bike share
- Company subsidized lunch program
Ideal candidate
Hands-on systems thinker who thrives at the science-engineering interface and loves turning research goals into robust automation. Collaborative, detail-oriented, and energized by fast-paced R&D and emerging lab technologies.
Requirements
- Bachelor's or advanced degree in Materials Science, Chemistry, Engineering, or related field
- Strong hands-on experience developing and scaling automated workflows in laboratory or industrial settings
- Understanding of Python programming, including API integration and error handling
- Understanding of CAD design and rapid prototyping, including 3D printing
- Hands-on experience with hardware systems including electrical wiring, sensors, liquid/gas plumbing, and PID controllers
- Familiarity with advanced experimental systems including vacuum, laser, furnace, and electrochemical experimentation
- Knowledge of machine vision applications and robotics control algorithms
- Proven ability to integrate hardware and controls systems with automation workflows
- Understanding of AI-driven decision-making in research automation
- Prior experience leading technical teams in a fast-paced R&D environment
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