{"schemaVersion":"jobsearcher.job.v1","id":"992a47786674d9c191696323","url":"https://jobsearcher.com/jobs/992a47786674d9c191696323","canonicalUrl":"https://jobsearcher.com/jobs/992a47786674d9c191696323","title":"Perception Engineer IV - Project Based","description":"This is a project-based employee role supporting the development, integration, and validation of ASI's autonomous reach stacker 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 IV develops and advances perception systems that enable ASI's autonomous reach stackers to understand container-yard environments, detect and track surrounding objects, identify containers and stacking locations, and safely perform material-handling operations. This role works with cameras, LiDAR, radar, GPS/GNSS, inertial sensors, and other sensing technologies to support environmental awareness, container detection, equipment tracking, precision alignment, obstacle avoidance, and autonomous task execution.\n\nAs a Level IV engineer within ASI's five-level engineering structure, this position independently leads complex perception features and subsystem initiatives from technical definition through integration and field validation. The role influences perception architecture, resolves difficult cross-system problems, and provides technical guidance to other engineers while collaborating with GNC, embedded software, systems, test, and field operations teams. Broader platform strategy and organization-wide technical direction remain aligned with engineering leadership and Level V technical authorities.\n\nESSENTIAL DUTIES AND RESPONSIBILITIES\n\nDesign, develop, integrate, and validate advanced perception algorithms for autonomous reach stacker applications\n\nLead complex perception features involving object detection, classification, segmentation, tracking, obstacle detection, free-space identification, and environmental modeling\n\nDevelop capabilities for detecting and tracking shipping containers, trucks, trailers, chassis, reach stackers, personnel, buildings, fences, and other yard objects\n\nDevelop perception solutions that support container identification, stack-position recognition, pickup and placement verification, and precision vehicle alignment\n\nProcess and fuse data from cameras, LiDAR, radar, GPS/GNSS, inertial sensors, encoders, and other vehicle systems\n\nDevelop environmental models that support navigation, motion planning, container handling, stacking, loading, unloading, and yard-management workflows\n\nLead defined perception workstreams from requirements development through architecture, implementation, integration, testing, and release\n\nContribute to perception architecture and technical design decisions for autonomous reach stacker platforms\n\nEstablish technical approaches, performance metrics, and acceptance criteria for complex perception capabilities\n\nIntegrate perception software with autonomous vehicle platforms, embedded computing systems, vehicle interfaces, and supporting autonomy software\n\nEvaluate perception performance using recorded datasets, simulation, software-in-the-loop testing, hardware-in-the-loop testing, and full-vehicle field validation\n\nAnalyze large datasets to identify false detections, missed detections, tracking failures, alignment errors, environmental limitations, and system-level edge cases\n\nDevelop and improve automated workflows for data collection, labeling, replay, regression testing, visualization, and performance analysis\n\nLead troubleshooting of complex issues involving sensor calibration, timing, synchronization, coordinate transformations, vehicle movement, computing performance, and system integration\n\nGuide sensor selection, placement, mounting, configuration, calibration, and validation activities on reach stacker platforms\n\nOptimize perception algorithms for real-time execution on embedded CPUs, GPUs, and other computing platforms\n\nCollaborate with GNC engineers to ensure perception outputs support safe navigation, motion planning, obstacle avoidance, container approach, and precision positioning\n\nPartner with systems engineers to define interfaces, requirements, failure responses, and operational constraints for perception subsystems\n\nWork with test engineers and field testers to develop comprehensive validation scenarios for container yards and intermodal environments\n\nInvestigate difficult field failures and lead the development and verification of corrective actions\n\nConduct design reviews and code reviews while providing technical feedback to other engineers\n\nMentor less-experienced engineers and support improvements to engineering practices, development tools, and team standards\n\nCommunicate technical risks, system limitations, findings, and recommendations to engineering teams and leadership\n\nDocument algorithms, architectures, interfaces, assumptions, test results, technical decisions, and known system limitations\n\nSupport customer demonstrations, field deployments, acceptance testing, 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 eight or more years of experience developing perception, computer vision, robotics, machine learning, sensor-fusion, or autonomous-system software\n\nAdvanced proficiency in C++ and Python\n\nDemonstrated experience independently developing and delivering complex perception features for robotic or autonomous systems\n\nStrong experience with computer vision, point-cloud processing, sensor fusion, object tracking, environmental modeling, or machine-learning algorithms\n\nExperience working with cameras, LiDAR, radar, GPS/GNSS, inertial sensors, or other robotic sensing technologies\n\nStrong understanding of coordinate systems, geometric transformations, sensor calibration, data synchronization, and three-dimensional geometry\n\nExperience designing software interfaces and integrating perception components into complex hardware and software systems\n\nExperience developing and optimizing real-time software for embedded or constrained computing platforms\n\nAdvanced experience 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, continuous integration, and configuration-management practices\n\nAbility to define meaningful performance metrics and use large datasets to evaluate perception-system performance\n\nDemonstrated ability to diagnose and resolve complex software, sensor, computing, and system-integration issues\n\nAbility to provide technical guidance and constructive feedback to other engineers\n\nStrong analytical, debugging, and technical problem-solving skills\n\nStrong written and verbal communication skills\n\nAbility to work effectively with engineering, operations, customer-facing, and field-testing 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 reach stackers, container-handling equipment, industrial vehicles, heavy equipment, or mobile robots\n\nFamiliarity with container yards, ports, intermodal terminals, distribution centers, or material-handling operations\n\nExperience with container detection, identification, pose estimation, stack-position recognition, or precision alignment applications\n\nFamiliarity with reach stacker spreaders, twistlocks, container pickup and placement, stacking workflows, or chassis-handling operations\n\nExperience with OpenCV, Point Cloud Library, PyTorch, TensorFlow, CUDA, TensorRT, or similar technologies\n\nExperience developing machine-learning solutions for detection, segmentation, classification, depth estimation, pose estimation, or tracking\n\nExperience with LiDAR point-cloud registration, filtering, clustering, mapping, and object detection\n\nExperience with multi-object tracking, occupancy grids, free-space detection, semantic mapping, or environmental modeling\n\nFamiliarity with Kalman filtering, Bayesian estimation, probabilistic robotics, or other sensor-fusion methods\n\nExperience optimizing software for GPUs, embedded computers, or real-time systems\n\nExperience with simulation, recorded-data replay, software-in-the-loop testing, and hardware-in-the-loop testing\n\nFamiliarity with functional safety principles and validation practices for autonomous or safety-critical systems\n\nExperience validating autonomous systems in industrial, outdoor, low-light, high-traffic, dusty, or weather-exposed 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.\n\nYour 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":"2026-07-07T04:20:05.317Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"17-2199.08","title":"Robotics Engineers","slug":"robotics-engineers"},{"code":"17-2199.00","title":"Engineers, All Other","slug":"engineers-all-other"}],"industries":[{"code":"541330","title":"Engineering Services","slug":"engineering-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"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 IV - Project Based","description":"This is a project-based employee role supporting the development, integration, and validation of ASI's autonomous reach stacker 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 IV develops and advances perception systems that enable ASI's autonomous reach stackers to understand container-yard environments, detect and track surrounding objects, identify containers and stacking locations, and safely perform material-handling operations. This role works with cameras, LiDAR, radar, GPS/GNSS, inertial sensors, and other sensing technologies to support environmental awareness, container detection, equipment tracking, precision alignment, obstacle avoidance, and autonomous task execution.\n\nAs a Level IV engineer within ASI's five-level engineering structure, this position independently leads complex perception features and subsystem initiatives from technical definition through integration and field validation. The role influences perception architecture, resolves difficult cross-system problems, and provides technical guidance to other engineers while collaborating with GNC, embedded software, systems, test, and field operations teams. Broader platform strategy and organization-wide technical direction remain aligned with engineering leadership and Level V technical authorities.\n\nESSENTIAL DUTIES AND RESPONSIBILITIES\n\nDesign, develop, integrate, and validate advanced perception algorithms for autonomous reach stacker applications\n\nLead complex perception features involving object detection, classification, segmentation, tracking, obstacle detection, free-space identification, and environmental modeling\n\nDevelop capabilities for detecting and tracking shipping containers, trucks, trailers, chassis, reach stackers, personnel, buildings, fences, and other yard objects\n\nDevelop perception solutions that support container identification, stack-position recognition, pickup and placement verification, and precision vehicle alignment\n\nProcess and fuse data from cameras, LiDAR, radar, GPS/GNSS, inertial sensors, encoders, and other vehicle systems\n\nDevelop environmental models that support navigation, motion planning, container handling, stacking, loading, unloading, and yard-management workflows\n\nLead defined perception workstreams from requirements development through architecture, implementation, integration, testing, and release\n\nContribute to perception architecture and technical design decisions for autonomous reach stacker platforms\n\nEstablish technical approaches, performance metrics, and acceptance criteria for complex perception capabilities\n\nIntegrate perception software with autonomous vehicle platforms, embedded computing systems, vehicle interfaces, and supporting autonomy software\n\nEvaluate perception performance using recorded datasets, simulation, software-in-the-loop testing, hardware-in-the-loop testing, and full-vehicle field validation\n\nAnalyze large datasets to identify false detections, missed detections, tracking failures, alignment errors, environmental limitations, and system-level edge cases\n\nDevelop and improve automated workflows for data collection, labeling, replay, regression testing, visualization, and performance analysis\n\nLead troubleshooting of complex issues involving sensor calibration, timing, synchronization, coordinate transformations, vehicle movement, computing performance, and system integration\n\nGuide sensor selection, placement, mounting, configuration, calibration, and validation activities on reach stacker platforms\n\nOptimize perception algorithms for real-time execution on embedded CPUs, GPUs, and other computing platforms\n\nCollaborate with GNC engineers to ensure perception outputs support safe navigation, motion planning, obstacle avoidance, container approach, and precision positioning\n\nPartner with systems engineers to define interfaces, requirements, failure responses, and operational constraints for perception subsystems\n\nWork with test engineers and field testers to develop comprehensive validation scenarios for container yards and intermodal environments\n\nInvestigate difficult field failures and lead the development and verification of corrective actions\n\nConduct design reviews and code reviews while providing technical feedback to other engineers\n\nMentor less-experienced engineers and support improvements to engineering practices, development tools, and team standards\n\nCommunicate technical risks, system limitations, findings, and recommendations to engineering teams and leadership\n\nDocument algorithms, architectures, interfaces, assumptions, test results, technical decisions, and known system limitations\n\nSupport customer demonstrations, field deployments, acceptance testing, 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 eight or more years of experience developing perception, computer vision, robotics, machine learning, sensor-fusion, or autonomous-system software\n\nAdvanced proficiency in C++ and Python\n\nDemonstrated experience independently developing and delivering complex perception features for robotic or autonomous systems\n\nStrong experience with computer vision, point-cloud processing, sensor fusion, object tracking, environmental modeling, or machine-learning algorithms\n\nExperience working with cameras, LiDAR, radar, GPS/GNSS, inertial sensors, or other robotic sensing technologies\n\nStrong understanding of coordinate systems, geometric transformations, sensor calibration, data synchronization, and three-dimensional geometry\n\nExperience designing software interfaces and integrating perception components into complex hardware and software systems\n\nExperience developing and optimizing real-time software for embedded or constrained computing platforms\n\nAdvanced experience 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, continuous integration, and configuration-management practices\n\nAbility to define meaningful performance metrics and use large datasets to evaluate perception-system performance\n\nDemonstrated ability to diagnose and resolve complex software, sensor, computing, and system-integration issues\n\nAbility to provide technical guidance and constructive feedback to other engineers\n\nStrong analytical, debugging, and technical problem-solving skills\n\nStrong written and verbal communication skills\n\nAbility to work effectively with engineering, operations, customer-facing, and field-testing 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 reach stackers, container-handling equipment, industrial vehicles, heavy equipment, or mobile robots\n\nFamiliarity with container yards, ports, intermodal terminals, distribution centers, or material-handling operations\n\nExperience with container detection, identification, pose estimation, stack-position recognition, or precision alignment applications\n\nFamiliarity with reach stacker spreaders, twistlocks, container pickup and placement, stacking workflows, or chassis-handling operations\n\nExperience with OpenCV, Point Cloud Library, PyTorch, TensorFlow, CUDA, TensorRT, or similar technologies\n\nExperience developing machine-learning solutions for detection, segmentation, classification, depth estimation, pose estimation, or tracking\n\nExperience with LiDAR point-cloud registration, filtering, clustering, mapping, and object detection\n\nExperience with multi-object tracking, occupancy grids, free-space detection, semantic mapping, or environmental modeling\n\nFamiliarity with Kalman filtering, Bayesian estimation, probabilistic robotics, or other sensor-fusion methods\n\nExperience optimizing software for GPUs, embedded computers, or real-time systems\n\nExperience with simulation, recorded-data replay, software-in-the-loop testing, and hardware-in-the-loop testing\n\nFamiliarity with functional safety principles and validation practices for autonomous or safety-critical systems\n\nExperience validating autonomous systems in industrial, outdoor, low-light, high-traffic, dusty, or weather-exposed 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.\n\nYour 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":"2026-07-07T04:20:05.317Z","dateModified":"2026-07-07T04:20:05.317Z","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":"992a47786674d9c191696323"},"url":"https://jobsearcher.com/jobs/992a47786674d9c191696323"}}