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Master’s degree in computer science, computer engineer, electrical engineer, mechanical engineer. Bachelor’s degree in either of the following: computer science, computer engineering, electrical engineer, mechanical engineer.
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Algorithm Development, Artificial Intelligence, Embedded Systems, Electronic Warfare, Image Processing, Machine Learning, Military Vehicles, Modeling/Simulation, Robotics/Automated Systems, Sensors Integration, System Engineering, Testing, Aerospace, Sensors/Optics, Autonomous Systems, Data Analytics/Science, ISR & Tactical Systems, Threat Systems.
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What we need to see: MS or PhD level education in Engineering or Computer Science with a focus on Deep Learning, Artificial Intelligence, or a related field, or equivalent experience. NVIDIA is looking for an experienced Machine Learning Engineer to join its Autonomous Vehicle team in Santa Clara, CA, USA. As a member of our team you will develop key features for our autonomous driving platform.
$176,000 - $333,500 a yearFull-timeExpandApply NowActive JobUpdated 9 days ago - UpvoteDownvoteShare Job
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0 years of related experience with a Masters’ degree in Electrical and Computer Engineering, Computational Science and Engineering, Computer Science, Modeling and Simulation, or related field of study.
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Masters or Phd in Electrical Engineering, Computer Engineering, Computer Science, or similar field of study. Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, or similar field of study.
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BS in STEM discipline including but not limited to Mechanical Engineering, Electrical Engineering, Computer Science or Optical Engineering. For the past decade, Luminar has built an advanced hardware and software/AI platform to enable its more than 50 industry partners, including the majority of global automotive OEMs. From consumer vehicle programs with Volvo Cars and Mercedes-Benz to technology partnerships including NVIDIA and Mobileye, Luminar is poised to be the first automotive technology company to enable next-generation safety and autonomous capabilities for global production vehicles.
$175,000 - $225,000 a yearFull-timeExpandApply NowActive JobUpdated 3 days ago - UpvoteDownvoteShare Job
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The SLU School of Science and Engineering is interdisciplinary by design bringing together engineering (Aerospace and Mechanical, Biomedical, Civil, and Electrical and Computer Engineering) with Aviation, Computer Science, Chemistry, Physics, and Earth and Atmospheric Sciences.
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Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars.
$116,000 - $224,250 a yearFull-timeExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.
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Master's or PhD degree in Aerospace Engineering, Electrical Engineering, Computer Science, Robotics or a related field. Design, develop, integrate and test inertial navigation systems (INS), GNSS products, visual navigation, and other related technologies for autonomous military vehicles (UAS, spacecraft, missiles, ground vehicles, underwater vehicles etc.
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Appraisal of current DoD investments in a broad range of areas: from human factors to autonomous systems, from materials science to nuclear weapons effects, from social behaviors to quantum computing.
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Proven experience in developing Navigation and Localization algorithms for autonomous vehicles, robotics, drones, maritime vehicles or similar application. Experience with sensor calibration, sensor fusion, state estimation, and SLAM (Simultaneous Localization and Mapping) techniques.
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Job Segment: Embedded, Systems Engineer, Mechanical Engineer, Computer Science, Technology, Engineering, Automotive. Bachelor’s degree in Mechanical Engineering, Electrical Engineering, Software Engineering, or Computer Science.
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Implement sensor fusion techniques to integrate data from multiple sensors such as GNSS, IMU, LIDAR, radar, sonar and cameras to enhance the accuracy and robustness of vehicle navigation where applicable.
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Basic Qualifications for Principal Level:Bachelor’s degree or higher in Computer Science, Computer Engineering, Electrical Engineering or other STEM (Science, Technology, Engineering or Mathematics) discipline with 5 years of software engineering experience (3 years for MS degree, 0 years for PhD)US Citizenship requiredExperience in software development using C.
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