As part of the machine-learning team, you will design and implement state-of-the-art machine learning algorithms for radar-based interactive sensors. You will design, develop, debug, and evaluate custom machine-learning algorithms that will be applied across a range of products and use cases. You will work closely with the team to improve algorithm performance and play an integral role enabling new state-of-the-art touchless interfaces.
3 Key Responsibilities
This role will involve the following:
-Design, develop, and evaluate novel machine learning algorithms for a custom radar sensor.
-Train, debug, fine tune, and optimize machine learning algorithms to achieve the ultimate user experience.
-Develop tools to help others train, test, and apply machine learning algorithms to a range of products and applications.
Master’s or Ph.D. degree in Machine Learning, Computer Science or related technical discipline.
3+ years experience in machine learning research for production systems.
Excellent Python/C/C++ programming skills.
Experience with a wide range of machine learning techniques, including at least one of the following: convolutional neural networks, generative adversarial networks, recurrent neural networks (LSTM, GRUs, etc.).
Experience developing novel machine learning architectures for at least one of the following: radar, LIDAR, audio, video, image recognition, inertial sensors (accelerometers or gyroscopes), other related sensors.
Solid foundation in computer science, with strong competencies in data structures, algorithms and software design.
Nice to have's
-Experience with Tensorflow or related machine learning libraries.
-Track history of publications in leading machine learning and/or HCI journals.
-Experience developing machine learning algorithms for interactive applications.
-Desire to work in a creative flexible atmosphere on the edge of research and production.
-Ability to communicate technical concepts clearly and effectively.
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