Research - Laboratory/Non-Laboratory, Staff/Administrative
Working at MIT offers opportunities, an environment, a culture - and benefits - that just aren't found together anywhere else. If you're curious, motivated, want to be part of a unique community, and help shape the future - then take a look at this opportunity.
MACHINE LEARNING ENGINEER , Brain and Cognitive Sciences (BCS) , to help tackle challenging problems at the intersection of brain science and artificial intelligence. Will join world-class neuroscientists and cognitive scientists in solving some of the today's most exciting computational research problems and apply machine learning, AI, and data science skills to cutting edge research on the brain and mind. Responsibilities include helping researchers develop large-scale neural network models of perception and cognition; helping translate computational algorithms into efficiently functioning (especially parallelized and GPU optimized) code; staying up-to-date with cutting edge computational techniques, including machine learning developments and aiding labs with integrating these techniques into their projects; providing guidance for storage and management of large data sets; and helping transition users to new computing tools. Will also interface with the MIT Quest for Intelligence, a multidisciplinary effort that aims to advance the science and engineering of human and machine intelligence. This effort seeks to discover the foundations of human intelligence, drive the development of technological tools that can accelerate progress in many fields, and spin off technological tools that can positively influence society. Will collaborate with the Quest engineering team to help develop the necessary services and infrastructure using the latest breakthroughs in artificial intelligence to accelerate research and education.
REQUIRED : advanced degree (M.S.) in machine learning or computer science; at least two years' relevant experience; extensive experience with CUDA; ability to write new CUDA operations with PyTorch and TensorFlow; extensive experience with GPU optimization in PyTorch and TensorFlow and with large-scale artificial neural networks; model parallelization experience; experience with parameter servers for hyperparameter search; and some knowledge of optimization theory. Job #16623
Internal Number: 16623
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