Perception Engineer III - Project Based
About The Position
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. The 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. 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 develop and validate reliable perception performance for autonomous dozers operating in uneven terrain, dust, changing ground conditions, and active work sites.
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 vehicles, construction equipment, heavy machinery, or mobile robots
- Knowledge of earthmoving, grading, cut-and-fill, site preparation, or construction 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 digital terrain models, elevation maps, traversability mapping, or surface reconstruction
- 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, off-road, construction, mining, or industrial environments
Responsibilities
- Develop, implement, integrate, and validate perception algorithms for autonomous dozer applications
- Contribute to perception capabilities involving obstacle detection, object classification, tracking, terrain understanding, traversability analysis, and work-area awareness
- Process and analyze data from cameras, LiDAR, radar, GPS/GNSS, inertial sensors, and other vehicle systems
- Develop and improve terrain models used to support autonomous navigation, path planning, grading, and earthmoving operations
- Support the detection and interpretation of terrain features, slopes, berms, drop-offs, spoil piles, work boundaries, equipment, personnel, and other operational hazards
- Contribute to multi-sensor fusion solutions that provide reliable environmental awareness in outdoor construction environments
- Own defined perception features and moderately complex assignments from development through integration, testing, and field validation
- Integrate perception software with ASI's autonomous dozer platforms and embedded computing systems
- Evaluate perception performance using recorded datasets, simulation, software-in-the-loop testing, hardware-in-the-loop testing, and 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, dozer operations, and autonomous task execution
- Work with test engineers and field testers to develop realistic 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
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
