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Broad understanding of methods and tooling, from traditional (FastCV) to deep learning approaches (i.e. PyTorch, Jax, Tensorflow) and their deployment to embedded systems (Android, C. Optimize machine learning model implementations and inference timesWork with TFLite, SNPE, or other embedded deep learning librariesQuantize and tune model architecture, speed, and performance while maintaining task performanceParticipate in rigorous benchmarking and analysis across model classesDeploy to mobile hardware running Android.
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The multi-disciplinary team consists of talented technical staff with expertise in electromagnetics, optics, signal processing (communication, GPS), RF design, statistics, optimization, computer vision, machine learning, autonomous control, software engineering, and embedded systems.
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Experience in design and development of embedded applications in autonomous vehicle software systems. Bachelor's degree in Robotics, Mechatronics, Computer Science, Engineering, a relevant field, or equivalent experience.
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DSP & Embedded Systems: Experience with real-time signal processing DSP platforms, embedded systems, and radar signal processing techniques. Educational Background: A master's or PhD in AI, Mathematics, Statistics, Physics, Electrical Engineering, Computer Engineering, or a related field.
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Research and develop in cutting-edge areas of Deep Learning, Machine Learning, and Computer Vision. Evaluate state-of-the-art algorithms for security surveillance applications that run on embedded devices and servers.
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Research and develop in cutting edge area of Deep Learning, Machine Learning and Computer Vision. Avigilon's Boston Development team is looking for a versatile and talented Research Engineer to work in a multidisciplinary team of Engineers and Research Engineers with the goal of building the next generation of artificial intelligence solutions for Video Surveillance and Business Intelligence.
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The ideal CRCS Postdoctoral Fellow will have a technical background in computer science (or related area) and a desire to creatively use those skills to address problems of societal importance.
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Bachelor's degree (or above) in a quantitative or computational field such as Statistics, Computer Science or Applied Mathematics. You will be 'embedded' within the quantitative research team and you will partner with the investment teams on various projects including portfolio construction, risk management, and alpha research.
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Experience with real-time image processing and embedded systems. Bachelor's or Master's degree in Computer Science, Electrical Engineering, Applied Mathematics, or a related field. Apply techniques in computer vision, machine learning, and deep learning to address complex challenges.
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Medical Devices - Embedded Software Test Engineer – Cambridge, MA. Bachelors or Masters Degree in Biomedical Engineering, Clinical Informatics, Clinical Engineering, Computer Science, or relevant technical experience.
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This Product Support Analyst role is embedded in our Data Science group. Solid foundation in computer networking and internet protocols. Data Science (DS) is a group of data engineering, curation, and data science professionals who are responsible for the analytics and data collection of many Recorded Future products.
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Perform expert-level engineering tasks associated with the analysis, design, and development of computer hardware, firmware, embedded systems, and/or operating systems. Perform expert-level engineering tasks associated with the analysis, design, and development of computer hardware, firmware, embedded systems, and/or operating systems.
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Experience integrating Machine Learning Deep learning and/or Computer Vision algorithms (OpenCV) on embedded hardware. We are seeking an active, hands-on, Software Engineering Manager who is passionate about the successful deployment of commercial systems employing deep learning and computer vision.
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Embedded Systems Testing: Collaborate with the firmware and hardware teams to ensure that embedded systems are thoroughly tested. Embedded Systems Knowledge: Strong understanding of embedded systems, sufficient to design and execute relevant test cases.
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Bachelor’s/Master’s Degree in Computer Science or Electrical Engineering and minimum 3-5 years development engineering or applications support of SoC based embedded systems. Knowledge in embedded Linux: kernel and user-space and uboot environments.
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embedded computer jobs in Cambridge, MA
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