Scientist, Flow Chemistry

Lila Sciences
Cambridge, MA USAPosted 26 March 2026

Tech Stack

Job Description

About Lila Sciences 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 At Lila, we are uniquely cross-functional and collaborative. We are actively reimagining the way teams work together and communicate. Therefore, we seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way. If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, please apply. Your Impact at Lila As a Scient ist on our Phy sical Sciences team, you will contribute to the development of cutting-edge flow chemistry workflows. You’ll help design, build, and optimize flow chemistry platforms that integrate real-time analytics, advanced control strategies, and AI-driven decision-making. In this role, you’ll work closely with systems engineers and AI scientists to help expand autonomous chemistry capabilities and accelerate discovery at scale. What You'll Be Building Design Commission: Architect and develop versatile flow chemistry platforms for autonomous synthesis, ensuring seamless integration with the Lila platform. Integrate Scale: B uild, control, and optimize flow reactors and inline analytics. Interface flow chemistry platforms with robotic and sensing systems. Workflow Optimization: Tune flow chemistry platform design and software pipelines for high-throughput closed-loop experimentation with rich metadata capture. Closed-Loop Execution: Collaborate with AI teams to run iterative experiments in real time, enabling fast optimization and discovery cycles. Collaboration Documentation: Work with chemists, material scientists, engineers, and data scientists to document systems, share insights, and refine best practices in autonomous flow chemistry. What You’ll Need to Succeed Ph.D. or M.S. in Chemical Engineering, Chemistry, or a related field. ≥ 1 years (for PhD, 4+ years for M.S ) of hands-on experience in flow chemistry, microfluidics, or microreaction engineering. ≥ 1 years of experience with automation, instrumentation, and integrating real-time analytics into experimental workflows. Strong background in homogeneous chemical catalysis and organic synthesis. Proficiency in Python for scripting, da ta analy sis, and instrument control. Excellent problem-solving, communication, and collaboration skills. Bonus Points For Prior experience working in an autonomous or self-driving lab chemical lab environment driving organic chemistry transformation s . Familiarity with cloud-based instrumentation control and orchestration. Hands-on experience with AI-driven experimental design or Bayesian optimization. Background in scaling workflows from proof-of-concept to routine, high-throughput operation. Contributions to open-source lab automation or scientific software projects. 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 mo ... (truncated, view full listing at source)
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