{"schemaVersion":"jobsearcher.job.v1","id":"e7d058fcb284da8fb6ca7613","url":"https://jobsearcher.com/jobs/e7d058fcb284da8fb6ca7613","canonicalUrl":"https://jobsearcher.com/jobs/e7d058fcb284da8fb6ca7613","title":"Perception Engineer III - Project Based","description":"This is a project-based employee role supporting the development, integration, and validation of ASI's autonomous agricultural vehicle platforms. Development phases of this nature typically continue through project completion, often spanning two to four years, although scope and duration are determined by business and customer needs.\n\nJOB SUMMARY\nThe Perception Engineer III develops, integrates, and validates perception capabilities that enable ASI's autonomous agricultural equipment to understand field conditions, detect obstacles, identify operational boundaries, and perform assigned tasks safely and effectively. This role works with data from cameras, LiDAR, radar, GPS/GNSS, inertial sensors, and other systems to support object detection, terrain understanding, crop and vegetation awareness, traversability analysis, and autonomous machine operation.\n\nAs a Level III engineer within ASI's five-level engineering structure, this position independently contributes to moderately complex perception features and subsystem improvements while receiving guidance on broader architectural and system-level decisions. The role collaborates with GNC, embedded software, systems, test, and field operations teams to improve perception performance across changing terrain, vegetation, lighting, weather, dust, and agricultural operating conditions.\n\nESSENTIAL DUTIES AND RESPONSIBILITIES\n\nDevelop, implement, integrate, and validate perception algorithms for autonomous agricultural vehicle applications\n\nContribute to capabilities involving obstacle detection, object classification, tracking, terrain understanding, traversability analysis, and operational-area awareness\n\nProcess and analyze data from cameras, LiDAR, radar, GPS/GNSS, inertial sensors, and other vehicle systems\n\nSupport perception of field boundaries, crop rows, vegetation, terrain features, equipment, personnel, animals, and other operational hazards\n\nDevelop and improve environmental models used to support autonomous navigation, path planning, and agricultural task execution\n\nContribute to multi-sensor fusion solutions that provide reliable environmental awareness in outdoor agricultural environments\n\nOwn defined perception features and moderately complex assignments from development through integration, testing, and field validation\n\nIntegrate perception software with ASI's autonomous agricultural platforms and embedded computing systems\n\nEvaluate perception performance using recorded datasets, simulation, software-in-the-loop testing, hardware-in-the-loop testing, and full-vehicle field testing\n\nDevelop measurable performance criteria for assigned perception features and use test results to identify improvement opportunities\n\nAnalyze field data to identify false detections, missed detections, edge cases, and environmental performance limitations\n\nDevelop tools and scripts for data processing, visualization, labeling, replay, regression testing, and performance analysis\n\nTroubleshoot issues involving sensor calibration, timing, synchronization, coordinate transformations, vehicle movement, and system integration\n\nSupport sensor selection, placement, mounting, configuration, calibration, and validation activities\n\nImprove perception software performance for real-time execution on embedded computing platforms\n\nCollaborate with GNC engineers to ensure perception outputs support navigation, path planning, obstacle avoidance, and autonomous task execution\n\nWork with test engineers and field testers to develop realistic agricultural test scenarios and reproduce perception-related issues\n\nParticipate in design reviews, code reviews, sprint planning, and technical investigations\n\nDocument algorithms, software interfaces, assumptions, test results, technical decisions, and known system limitations\n\nSupport field deployments, customer demonstrations, and troubleshooting activities as required\n\nESSENTIAL EDUCATION, WORK EXPERIENCE, JOB SKILLS\n\nBachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, Mathematics, or a related technical field\n\nTypically five or more years of experience developing perception, computer vision, robotics, machine learning, sensor-fusion, or autonomous-system software\n\nStrong proficiency in C++ and Python\n\nExperience developing or integrating computer vision, point-cloud processing, sensor-fusion, or machine-learning algorithms\n\nExperience working with cameras, LiDAR, radar, GPS/GNSS, or other robotic sensing technologies\n\nUnderstanding of coordinate systems, transformations, sensor calibration, data synchronization, and geometric algorithms\n\nExperience working in Linux-based software-development environments\n\nExperience with ROS, ROS2, or comparable robotics middleware\n\nExperience developing production-quality software using version control, peer review, automated testing, and continuous integration practices\n\nAbility to analyze large datasets and establish measurable criteria for evaluating algorithm performance\n\nExperience troubleshooting software, sensor, and system-integration issues\n\nStrong analytical, debugging, and technical problem-solving skills\n\nStrong written and verbal communication skills\n\nAbility to work effectively with cross-functional engineering and field teams\n\nPREFERRED QUALIFICATIONS\n\nMaster's degree in Computer Science, Electrical Engineering, Robotics, Machine Learning, or a related discipline\n\nExperience developing perception systems for autonomous agricultural equipment, off-road vehicles, heavy machinery, or mobile robots\n\nFamiliarity with agricultural operations, field navigation, crop production, spraying, planting, harvesting, or related workflows\n\nExperience with OpenCV, Point Cloud Library, PyTorch, TensorFlow, CUDA, or similar technologies\n\nExperience with machine-learning approaches for detection, segmentation, classification, depth estimation, or tracking\n\nExperience with LiDAR point-cloud registration, clustering, filtering, mapping, or ground-surface analysis\n\nFamiliarity with crop-row detection, vegetation segmentation, field-boundary detection, elevation mapping, or traversability analysis\n\nFamiliarity with Kalman filtering, Bayesian estimation, probabilistic robotics, or other sensor-fusion methods\n\nExperience optimizing perception software for GPUs or embedded computing platforms\n\nExperience with simulation, recorded-data replay, hardware-in-the-loop, or software-in-the-loop testing\n\nFamiliarity with functional safety concepts and validation practices for autonomous or safety-critical systems\n\nExperience validating autonomous systems in dusty, high-vibration, uneven, outdoor, agricultural, or industrial environments\n\nBENEFITS\nASI offers a comprehensive benefits package, including:\n\n401k with employer match\n\nGenerous HSA contribution\n\nPTO, paid holidays, and flextime\n\nASI covers 90% of employee medical plan costs\n\nAt Autonomous Solutions, Inc. (ASI), we are committed to fostering a diverse, inclusive, and equitable workplace where all employees and applicants have equal opportunities. We prohibit discrimination and harassment of any kind based on race, color, religion, sex, national origin, age, disability, genetic information, veteran status, sexual orientation, gender identity, or any other legally protected characteristic. ASI complies with all applicable federal, state, and local laws regarding nondiscrimination in employment and is dedicated to providing reasonable accommodations for individuals with disabilities throughout the hiring process.\n\nThis is a full-time, project-based employment opportunity. Your employment with ASI will be \"at will,\" meaning that either you or ASI may terminate your employment at any time for any lawful reason, with or without cause or advance notice.\n\n#J-18808-Ljbffr","company":"Autonomous Solutions","rawCompany":"autonomous solutions","city":"Mendon","state":"UT","isRemote":false,"isActive":true,"createdAt":"2026-07-08T03:28:33.116Z","occupations":[{"code":"17-2199.08","title":"Robotics Engineers","slug":"robotics-engineers"},{"code":"17-2199.00","title":"Engineers, All Other","slug":"engineers-all-other"},{"code":"17-2021.00","title":"Agricultural Engineers","slug":"agricultural-engineers"}],"industries":[{"code":"541330","title":"Engineering Services","slug":"engineering-services"},{"code":"541715","title":"Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)","slug":"research-and-development-in-the-physical-engineering-and-life-sciences-except-nanotechnology-and-biotechnology"},{"code":"336110","title":"Automobile and Light Duty Motor Vehicle Manufacturing","slug":"automobile-and-light-duty-motor-vehicle-manufacturing"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Perception Engineer III - Project Based","description":"This is a project-based employee role supporting the development, integration, and validation of ASI's autonomous agricultural vehicle platforms. Development phases of this nature typically continue through project completion, often spanning two to four years, although scope and duration are determined by business and customer needs.\n\nJOB SUMMARY\nThe Perception Engineer III develops, integrates, and validates perception capabilities that enable ASI's autonomous agricultural equipment to understand field conditions, detect obstacles, identify operational boundaries, and perform assigned tasks safely and effectively. This role works with data from cameras, LiDAR, radar, GPS/GNSS, inertial sensors, and other systems to support object detection, terrain understanding, crop and vegetation awareness, traversability analysis, and autonomous machine operation.\n\nAs a Level III engineer within ASI's five-level engineering structure, this position independently contributes to moderately complex perception features and subsystem improvements while receiving guidance on broader architectural and system-level decisions. The role collaborates with GNC, embedded software, systems, test, and field operations teams to improve perception performance across changing terrain, vegetation, lighting, weather, dust, and agricultural operating conditions.\n\nESSENTIAL DUTIES AND RESPONSIBILITIES\n\nDevelop, implement, integrate, and validate perception algorithms for autonomous agricultural vehicle applications\n\nContribute to capabilities involving obstacle detection, object classification, tracking, terrain understanding, traversability analysis, and operational-area awareness\n\nProcess and analyze data from cameras, LiDAR, radar, GPS/GNSS, inertial sensors, and other vehicle systems\n\nSupport perception of field boundaries, crop rows, vegetation, terrain features, equipment, personnel, animals, and other operational hazards\n\nDevelop and improve environmental models used to support autonomous navigation, path planning, and agricultural task execution\n\nContribute to multi-sensor fusion solutions that provide reliable environmental awareness in outdoor agricultural environments\n\nOwn defined perception features and moderately complex assignments from development through integration, testing, and field validation\n\nIntegrate perception software with ASI's autonomous agricultural platforms and embedded computing systems\n\nEvaluate perception performance using recorded datasets, simulation, software-in-the-loop testing, hardware-in-the-loop testing, and full-vehicle field testing\n\nDevelop measurable performance criteria for assigned perception features and use test results to identify improvement opportunities\n\nAnalyze field data to identify false detections, missed detections, edge cases, and environmental performance limitations\n\nDevelop tools and scripts for data processing, visualization, labeling, replay, regression testing, and performance analysis\n\nTroubleshoot issues involving sensor calibration, timing, synchronization, coordinate transformations, vehicle movement, and system integration\n\nSupport sensor selection, placement, mounting, configuration, calibration, and validation activities\n\nImprove perception software performance for real-time execution on embedded computing platforms\n\nCollaborate with GNC engineers to ensure perception outputs support navigation, path planning, obstacle avoidance, and autonomous task execution\n\nWork with test engineers and field testers to develop realistic agricultural test scenarios and reproduce perception-related issues\n\nParticipate in design reviews, code reviews, sprint planning, and technical investigations\n\nDocument algorithms, software interfaces, assumptions, test results, technical decisions, and known system limitations\n\nSupport field deployments, customer demonstrations, and troubleshooting activities as required\n\nESSENTIAL EDUCATION, WORK EXPERIENCE, JOB SKILLS\n\nBachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, Mathematics, or a related technical field\n\nTypically five or more years of experience developing perception, computer vision, robotics, machine learning, sensor-fusion, or autonomous-system software\n\nStrong proficiency in C++ and Python\n\nExperience developing or integrating computer vision, point-cloud processing, sensor-fusion, or machine-learning algorithms\n\nExperience working with cameras, LiDAR, radar, GPS/GNSS, or other robotic sensing technologies\n\nUnderstanding of coordinate systems, transformations, sensor calibration, data synchronization, and geometric algorithms\n\nExperience working in Linux-based software-development environments\n\nExperience with ROS, ROS2, or comparable robotics middleware\n\nExperience developing production-quality software using version control, peer review, automated testing, and continuous integration practices\n\nAbility to analyze large datasets and establish measurable criteria for evaluating algorithm performance\n\nExperience troubleshooting software, sensor, and system-integration issues\n\nStrong analytical, debugging, and technical problem-solving skills\n\nStrong written and verbal communication skills\n\nAbility to work effectively with cross-functional engineering and field teams\n\nPREFERRED QUALIFICATIONS\n\nMaster's degree in Computer Science, Electrical Engineering, Robotics, Machine Learning, or a related discipline\n\nExperience developing perception systems for autonomous agricultural equipment, off-road vehicles, heavy machinery, or mobile robots\n\nFamiliarity with agricultural operations, field navigation, crop production, spraying, planting, harvesting, or related workflows\n\nExperience with OpenCV, Point Cloud Library, PyTorch, TensorFlow, CUDA, or similar technologies\n\nExperience with machine-learning approaches for detection, segmentation, classification, depth estimation, or tracking\n\nExperience with LiDAR point-cloud registration, clustering, filtering, mapping, or ground-surface analysis\n\nFamiliarity with crop-row detection, vegetation segmentation, field-boundary detection, elevation mapping, or traversability analysis\n\nFamiliarity with Kalman filtering, Bayesian estimation, probabilistic robotics, or other sensor-fusion methods\n\nExperience optimizing perception software for GPUs or embedded computing platforms\n\nExperience with simulation, recorded-data replay, hardware-in-the-loop, or software-in-the-loop testing\n\nFamiliarity with functional safety concepts and validation practices for autonomous or safety-critical systems\n\nExperience validating autonomous systems in dusty, high-vibration, uneven, outdoor, agricultural, or industrial environments\n\nBENEFITS\nASI offers a comprehensive benefits package, including:\n\n401k with employer match\n\nGenerous HSA contribution\n\nPTO, paid holidays, and flextime\n\nASI covers 90% of employee medical plan costs\n\nAt Autonomous Solutions, Inc. (ASI), we are committed to fostering a diverse, inclusive, and equitable workplace where all employees and applicants have equal opportunities. We prohibit discrimination and harassment of any kind based on race, color, religion, sex, national origin, age, disability, genetic information, veteran status, sexual orientation, gender identity, or any other legally protected characteristic. ASI complies with all applicable federal, state, and local laws regarding nondiscrimination in employment and is dedicated to providing reasonable accommodations for individuals with disabilities throughout the hiring process.\n\nThis is a full-time, project-based employment opportunity. Your employment with ASI will be \"at will,\" meaning that either you or ASI may terminate your employment at any time for any lawful reason, with or without cause or advance notice.\n\n#J-18808-Ljbffr","datePosted":"2026-07-08T03:28:33.116Z","dateModified":"2026-07-08T03:28:33.116Z","hiringOrganization":{"@type":"Organization","name":"Autonomous Solutions","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Mendon","addressRegion":"UT","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"e7d058fcb284da8fb6ca7613"},"url":"https://jobsearcher.com/jobs/e7d058fcb284da8fb6ca7613"}}