AI training and inference clusters produce large, fast, synchronized power swings. A single GPU rack can move more than half of its rated load in milliseconds, and when hundreds of racks move together the effect reaches the facility boundary and the grid. We are developing a hybrid energy storage system for data centers to protect upstream infrastructure and increase usable capacity. We are seeking a Research Intern (Hardware Implementation and Validation) to take this system from design to hardware. You will own the implementation and validation of the storage system and its controllers, compare the design's predicted behavior against what the hardware actually does, and feed the differences back into the design. Where the measurements show that the architecture, sizing, or control law needs to change, you will propose and implement the change. This is a hands-on engineering role with a research component. Results are expected to be reported internally and, where appropriate, to feed conference publications and standards discussions.
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Job Type
Full-time
Career Level
Intern