{"schemaVersion":"jobsearcher.job.v1","id":"2ff19e2e55ff0d0d5f179549","url":"https://jobsearcher.com/jobs/2ff19e2e55ff0d0d5f179549","canonicalUrl":"https://jobsearcher.com/jobs/2ff19e2e55ff0d0d5f179549","title":"Perception Engineer III - Project Based","description":"This is a project-based employee role supporting the development, integration, and validation of ASI's autonomous dozer 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 dozers to understand terrain, detect obstacles, recognize work‑area conditions, and operate safely in dynamic construction and earthmoving environments. This role works with data from cameras, LiDAR, radar, GPS/GNSS, inertial sensors, and other systems to support terrain modeling, obstacle detection, traversability analysis, localization, and autonomous machine behavior.\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 develop and validate reliable perception performance for autonomous dozers operating in uneven terrain, dust, changing ground conditions, and active work sites.\n\nESSENTIAL DUTIES AND RESPONSIBILITIES\n\nDevelop, implement, integrate, and validate perception algorithms for autonomous dozer applications\n\nContribute to perception capabilities involving obstacle detection, object classification, tracking, terrain understanding, traversability analysis, and work‑area awareness\n\nProcess and analyze data from cameras, LiDAR, radar, GPS/GNSS, inertial sensors, and other vehicle systems\n\nDevelop and improve terrain models used to support autonomous navigation, path planning, grading, and earthmoving operations\n\nSupport the detection and interpretation of terrain features, slopes, berms, drop‑offs, spoil piles, work boundaries, equipment, personnel, and other operational hazards\n\nContribute to multi‑sensor fusion solutions that provide reliable environmental awareness in outdoor construction 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 dozer platforms and embedded computing systems\n\nEvaluate perception performance using recorded datasets, simulation, software‑in‑the‑loop testing, hardware‑in‑the‑loop testing, and 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, dozer operations, and autonomous task execution\n\nWork with test engineers and field testers to develop realistic 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 vehicles, construction equipment, heavy machinery, or mobile robots\n\nKnowledge of earthmoving, grading, cut‑and‑fill, site preparation, or construction 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, and ground‑surface analysis\n\nFamiliarity with digital terrain models, elevation maps, traversability mapping, or surface reconstruction\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, off‑road, construction, mining, 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":"Fort Worth","state":"TX","isRemote":false,"isActive":true,"createdAt":"2026-07-08T03:31:00.426Z","occupations":[{"code":"17-2199.00","title":"Engineers, All Other","slug":"engineers-all-other"},{"code":"17-2199.08","title":"Robotics Engineers","slug":"robotics-engineers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541330","title":"Engineering Services","slug":"engineering-services"},{"code":"237990","title":"Other Heavy and Civil Engineering Construction","slug":"other-heavy-and-civil-engineering-construction"},{"code":"333120","title":"Construction Machinery Manufacturing","slug":"construction-machinery-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 dozer 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 dozers to understand terrain, detect obstacles, recognize work‑area conditions, and operate safely in dynamic construction and earthmoving environments. This role works with data from cameras, LiDAR, radar, GPS/GNSS, inertial sensors, and other systems to support terrain modeling, obstacle detection, traversability analysis, localization, and autonomous machine behavior.\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 develop and validate reliable perception performance for autonomous dozers operating in uneven terrain, dust, changing ground conditions, and active work sites.\n\nESSENTIAL DUTIES AND RESPONSIBILITIES\n\nDevelop, implement, integrate, and validate perception algorithms for autonomous dozer applications\n\nContribute to perception capabilities involving obstacle detection, object classification, tracking, terrain understanding, traversability analysis, and work‑area awareness\n\nProcess and analyze data from cameras, LiDAR, radar, GPS/GNSS, inertial sensors, and other vehicle systems\n\nDevelop and improve terrain models used to support autonomous navigation, path planning, grading, and earthmoving operations\n\nSupport the detection and interpretation of terrain features, slopes, berms, drop‑offs, spoil piles, work boundaries, equipment, personnel, and other operational hazards\n\nContribute to multi‑sensor fusion solutions that provide reliable environmental awareness in outdoor construction 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 dozer platforms and embedded computing systems\n\nEvaluate perception performance using recorded datasets, simulation, software‑in‑the‑loop testing, hardware‑in‑the‑loop testing, and 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, dozer operations, and autonomous task execution\n\nWork with test engineers and field testers to develop realistic 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 vehicles, construction equipment, heavy machinery, or mobile robots\n\nKnowledge of earthmoving, grading, cut‑and‑fill, site preparation, or construction 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, and ground‑surface analysis\n\nFamiliarity with digital terrain models, elevation maps, traversability mapping, or surface reconstruction\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, off‑road, construction, mining, 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":"2026-07-08T03:31:00.426Z","dateModified":"2026-07-08T03:31:00.426Z","hiringOrganization":{"@type":"Organization","name":"Autonomous Solutions","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Fort Worth","addressRegion":"TX","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"2ff19e2e55ff0d0d5f179549"},"url":"https://jobsearcher.com/jobs/2ff19e2e55ff0d0d5f179549"}}