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Salary: USD 118,800 - 182,400 / annual
Lila Sciences is seeking a Senior Automated Systems Engineer to design, develop, and implement automation solutions for laboratory workflows. Reporting to the Automated Systems Engineering Lead, you will build scalable, high-throughput automated workcells that translate scientific intent into reliable, real-world systems.
You will serve as a steward of scientific and cross-functional requirements, working closely with scientists, hardware, controls, and software teams to define scope, align interfaces, and drive projects from concept through deployment. Key responsibilities include:
• Contribute hands-on to development, testing, and implementation of automated workflows in the lab
• Develop scalable automated solutions for synthesis and characterization workflows supporting porous materials, catalysts, coatings, and advanced composites
• Define and document standardized laboratory workflows, operating procedures, and system architectures
• Lead and participate in equipment- and system-level FMEAs to improve robustness and safety
• Troubleshoot and optimize automated systems for throughput, reliability, and adaptability
• Design failure detection methods and maintain laboratory automation systems
• Translate scientific objectives into well-scoped technical requirements and automation architectures
• Act as connective tissue between science, hardware, controls, and software teams
• Explore and integrate emerging technologies such as machine vision and advanced sensors
• Ensure alignment with safety, quality, and regulatory standards
Required qualifications include strong hands-on experience developing and scaling automated workflows in laboratory or industrial settings; Python programming with API integration and error handling; CAD design and rapid prototyping experience; hands-on hardware systems knowledge (electrical wiring, sensors, plumbing, PID controllers); critical thinking and collaborative skills; and familiarity with advanced experimental systems (vacuum, laser, furnace, electrochemical). Preferred experience includes machine vision, robotics control algorithms, hardware-controls integration, and AI-driven decision-making in research automation.
