Perception Engineer III - Project Based

Autonomous Solutions • Mendon, UT

1d • Onsite

About The Position

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. The 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. As 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.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, Mathematics, or a related technical field
• Typically five or more years of experience developing perception, computer vision, robotics, machine learning, sensor-fusion, or autonomous-system software
• Strong proficiency in C++ and Python
• Experience developing or integrating computer vision, point-cloud processing, sensor-fusion, or machine-learning algorithms
• Experience working with cameras, LiDAR, radar, GPS/GNSS, or other robotic sensing technologies
• Understanding of coordinate systems, transformations, sensor calibration, data synchronization, and geometric algorithms
• Experience working in Linux-based software-development environments
• Experience with ROS, ROS2, or comparable robotics middleware
• Experience developing production-quality software using version control, peer review, automated testing, and continuous integration practices
• Ability to analyze large datasets and establish measurable criteria for evaluating algorithm performance
• Experience troubleshooting software, sensor, and system-integration issues
• Strong analytical, debugging, and technical problem-solving skills
• Strong written and verbal communication skills
• Ability to work effectively with cross-functional engineering and field teams

Nice To Haves

• Master's degree in Computer Science, Electrical Engineering, Robotics, Machine Learning, or a related discipline
• Experience developing perception systems for autonomous agricultural equipment, off-road vehicles, heavy machinery, or mobile robots
• Familiarity with agricultural operations, field navigation, crop production, spraying, planting, harvesting, or related workflows
• Experience with OpenCV, Point Cloud Library, PyTorch, TensorFlow, CUDA, or similar technologies
• Experience with machine-learning approaches for detection, segmentation, classification, depth estimation, or tracking
• Experience with LiDAR point-cloud registration, clustering, filtering, mapping, or ground-surface analysis
• Familiarity with crop-row detection, vegetation segmentation, field-boundary detection, elevation mapping, or traversability analysis
• Familiarity with Kalman filtering, Bayesian estimation, probabilistic robotics, or other sensor-fusion methods
• Experience optimizing perception software for GPUs or embedded computing platforms
• Experience with simulation, recorded-data replay, hardware-in-the-loop, or software-in-the-loop testing
• Familiarity with functional safety concepts and validation practices for autonomous or safety-critical systems
• Experience validating autonomous systems in dusty, high-vibration, uneven, outdoor, agricultural, or industrial environments

Responsibilities

• Develop, implement, integrate, and validate perception algorithms for autonomous agricultural vehicle applications
• Contribute to capabilities involving obstacle detection, object classification, tracking, terrain understanding, traversability analysis, and operational-area awareness
• Process and analyze data from cameras, LiDAR, radar, GPS/GNSS, inertial sensors, and other vehicle systems
• Support perception of field boundaries, crop rows, vegetation, terrain features, equipment, personnel, animals, and other operational hazards
• Develop and improve environmental models used to support autonomous navigation, path planning, and agricultural task execution
• Contribute to multi-sensor fusion solutions that provide reliable environmental awareness in outdoor agricultural environments
• Own defined perception features and moderately complex assignments from development through integration, testing, and field validation
• Integrate perception software with ASI's autonomous agricultural platforms and embedded computing systems
• Evaluate perception performance using recorded datasets, simulation, software-in-the-loop testing, hardware-in-the-loop testing, and full-vehicle field testing
• Develop measurable performance criteria for assigned perception features and use test results to identify improvement opportunities
• Analyze field data to identify false detections, missed detections, edge cases, and environmental performance limitations
• Develop tools and scripts for data processing, visualization, labeling, replay, regression testing, and performance analysis
• Troubleshoot issues involving sensor calibration, timing, synchronization, coordinate transformations, vehicle movement, and system integration
• Support sensor selection, placement, mounting, configuration, calibration, and validation activities
• Improve perception software performance for real-time execution on embedded computing platforms
• Collaborate with GNC engineers to ensure perception outputs support navigation, path planning, obstacle avoidance, and autonomous task execution
• Work with test engineers and field testers to develop realistic agricultural test scenarios and reproduce perception-related issues
• Participate in design reviews, code reviews, sprint planning, and technical investigations
• Document algorithms, software interfaces, assumptions, test results, technical decisions, and known system limitations
• Support field deployments, customer demonstrations, and troubleshooting activities as required

Benefits

• 401k with employer match
• Generous HSA contribution
• PTO, paid holidays, and flextime
• ASI covers 90% of employee medical plan costs

What This Job Offers

• Job Type: Full-time
• Career Level: Senior