Staff Forward Deployed Engineer, Physical Sciences (Level Flexible)

Lila Sciences
Cambridge, MA USAPosted 26 March 2026

Job Description

Your Impact at Lila We're seeking extraordinarily talented Forward Deployed Engineers across Engineer, Senior Engineer, and Lead Engineer levels to join our growing team. Our FDEs are high-performing generalists with a broad set of skills, in addition to depth in one or more focus areas. This FDE, Physical Sciences role requires experience in chemistry and materials science in an industrial manufacturing setting. As an FDE, you'll embed directly with our internal biotech and materials science teams as well as external customers, living their problems and rapidly building solutions that transform their research capabilities. You'll leverage our AI and software platform tools while developing bespoke features that address each customer's unique challenges. This isn't traditional software development—it's high-velocity, AI-fueled, high-impact engineering where you'll ship production code in days, not months. What You'll Be Building Developing, wrapping, and adapting domain-specific tools for data analysis, process optimization, molecular modeling, and more Deploying custom, agentic scientific workflows that integrate with industrial instruments (PLCs, control software) and data systems (ERP, MES, SCADA) Building real-time data pipelines that transform messy scientific data into actionable insights Creating intuitive interfaces that make complex AI/ML capabilities accessible to scientists Architecting solutions that scale from proof-of-concept to enterprise-wide deployment What You'll Need to Succeed Domain expertise in chemistry, materials science, or related field Outstanding communication skills—you'll interface directly with both executives and the manufacturing line Experience with data engineering, ETL pipelines, and working with complex/messy datasets Strong full-stack development skills with the ability to work across backend, frontend, and data layers Exceptional problem-solving abilities and comfort with ambiguous requirements Knack for product discovery and ability to pass requirements back to the platform Willingness to travel to customer sites for frequent and extended deployments Bonus Points For Previous customer-facing or consulting experience Depth in controls engineering and machine learning Experience with scientific computing libraries (NumPy, Pandas, SciPy, RDKit) Familiarity with ML/AI implementation and deployment Familiarity with modern web technologies (TypeScript, React) What Makes a Great FDE Customer Obsessed : You're energized by understanding customer problems deeply and seeing your solutions drive real impact Fast Learner : You quickly grasp new scientific domains and translate complex requirements into elegant solutions Autonomous : You thrive with minimal supervision and take extreme ownership of customer success Collaborative : You work seamlessly with both technical and non-technical stakeholders Technically Versatile : You're comfortable jumping between technologies and picking up new tools as needed Ready to Transform Scientific Discovery? If you're excited about embedding with world-class scientists, shipping impactful solutions at startup speed, and building the future of scientific software, we want to hear from you. Join us in our mission to accelerate breakthrough discoveries that will define the next century of human progress. About Lila Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science.  We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method.  We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at www.lila.ai If this sounds like an environment you’d love to work in, even if you only have some o ... (truncated, view full listing at source)
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