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Samsung SDI America Inc

Automation Engineer

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Job Description

Samsung SDI Research America (SDIRA), based in Cambridge, MA, is one of several newly established global battery R&D centers created to foster cutting edge research and pioneer the development of Samsung's next-generation cell technologies. The location is close to world-renowned universities and start-up companies, enabling unique collaborative research within a strong North American ecosystem of battery development expertise.
Work Location:
Boston, MA Responsibilities Develop, optimize, and maintain control software that coordinates sensors, actuators, and a wide range of laboratory equipment Design control logics and algorithms for high-throughput experimentation Build function-specific devices/tools to address challenges and inefficiencies in automated workflows Identify technical requirements and risks associated with the buildout of the high-throughput experiment platform, and propose actionable solutions/strategies Collaborate with a multidisciplinary team of scientists and engineers in a fast-moving environment Produce concise technical reports and presentations for efficient communication of project status Required qualifications Bachelor's degree in Mechanical, Electrical, Computer Engineering, Mechatronics or a related field Minimum of 2 years of relevant experience (including advanced degrees in relevant fields) Proficiency in Python, C/C++ or similar programming languages Proficiency in version control tools (e.g., SVN/Git/GitLab/GitHub) Experience in microcontroller development (e.g., Arduino, Raspberry Pi) Experience in prototyping custom devices/mechanisms and sensor/motor integration Familiarity with communication protocols (e.g., TCP/IP, RS-232) Preferred qualifications Master's degree in Mechanical, Electrical, Computer Engineering, Mechatronics or a related field Experience with CAD and 3D printing Familiarity with materials development R&D Familiarity with database platforms (e.g., MongoDB, influxDB, questDB) Experience implementing ML and Bayesian optimization frameworks (e.g., PyTorch, TensorFlow, BoTorch)