Job description

At Meta, we are looking for an experienced and motivated engineer to define and drive the software orchestration and physical infrastructure for our autonomous, "self-driving" battery research lab. In this role, you will lead the technical build-out of connected, multi-station automated workcells and guide the architecture for APIs and data pipelines required to bridge laboratory hardware with advanced machine learning pipelines. Collaborating closely with a cross-functional team of materials scientists and ML engineers, your orchestration platform will directly accelerate the closed-loop discovery and deployment of next-generation battery technologies for next-generation devices. Define the overall technical roadmap and detailed system architecture to build an autonomous, automated, end-to-end battery research lab, seamlessly integrating both commercially available instruments and custom hardware solutions Identify gaps where commercial automation solutions fall short. Define strategies for external partner engagement and directly lead the co-development of custom automation approaches with third-party vendors. Own build-out of partner automation solutions within Meta labs. Drive or directly develop application-specific customizations and extensions of automation solutions Guide development of software by internal and/or external partners to operate individual system components, orchestrate the full system, and provide resulting data to researchers Translate the needs of internal research scientists into actionable hardware and software engineering specifications for the autonomous lab system, ensuring continuous alignment with core research objectives Bachelor's degree in Robotics, Mechatronics, Electrical Engineering, Computer Science, Mechanical Engineering, or a related technical discipline 8+ years of hands-on experience designing, scaling, and deploying automated laboratory systems, robotic workcells, or complex industrial testing/characterization hardware Experience setting requirements for and using software to control physical hardware, manage device state machines, sequence multi-instrument workflows. Experience setting requirements for custom APIs, web services, or serial communication protocols to bridge data and control pathways between different vendor instruments Experience managing technical definitions, timelines, and deliverables with third-party automation vendors, system integrators, or external OEM partners Experience collaborating with cross-functional teams (e.g., research scientists, software engineers, hardware engineers) to translate scientific experimental requirements into engineering specifications Master's or Ph.D. in Robotics, Mechatronics, Computer Science, or a related field with a thesis or research focus on automated physical systems Familiarity with modern laboratory connectivity standards and middleware protocols Experience integrating automated hardware with Electronic Laboratory Notebooks (ELNs), Laboratory Information Management Systems (LIMS), or centralized cloud data warehouses Experience with battery and materials characterization techniques, including electrochemical cell characterization, cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), X-ray photoelectron spectroscopy (XPS), and Fourier-transform infrared spectroscopy (FTIR) Experience with industrial lab orchestration/scheduling software or data workflow management tools Direct experience working on automated high-throughput screening (HTS) or "closed-loop" autonomous discovery systems where hardware execution loops were driven by algorithmic/ML inputs

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Keywords to mirror

machine learningml

Platform: meta
Effort: medium