Software Perception Engineer

The Sr. Software Perception Engineer designs, implements, and tests advanced perception algorithms for mobile off-road machines, focusing on sensor fusion, object detection, tracking, and classification. In this role, you collaborate closely with engineers and researchers to integrate perception solutions into a broader software stack and hardware platform, ensuring high performance, safety, and reliability. You contribute to the full lifecycle of perception software, from architecture and design through verification, validation, and continuous improvement driven by real-world customer data., * Design, implement, and test algorithms for sensor fusion, object detection, tracking, and classification to support mobile off-road machines and autonomy features.

• Participate in the design and development of high-quality perception software and algorithms that address customer needs and improve machine safety and productivity.
• Collaborate with application teams to collect and analyze data from robotic and manned platforms, focusing on customer experience and system performance.
• Analyze and annotate perception data for machine learning training, and actively participate in iterative ML training cycles to meet perception performance requirements.
• Document architecture specifications, software designs, verification plans, test cases, operating procedures, and safety procedures in a clear and comprehensive manner.
• Use appropriate debugging, testing, and maintenance tools to ensure perception software quality and to support verification and validation processes.
• Design, write, test, and review autonomy and advanced operator-assist perception software, ensuring adherence to best practices and coding standards.
• Contribute to efforts to develop, integrate, and test complex autonomy systems that meet prioritized requirements and schedule constraints for autonomous machine programs.
• Focus development and integration activities on enhancing machine safety, productivity, and overall system robustness.
• Solve complex issues that span multiple subsystems, working across hardware, software, and data pipelines to identify root causes and implement effective solutions.
• Work independently on assigned tasks while actively collaborating within a multidisciplinary team to achieve project goals.
• Use Agile software development methodologies and modern development tools to plan, track, and deliver perception software features and improvements., Agile Methodology Business Valuation Software Solutions Amazon Web Services Software Engineering Software Development Cloud Infrastructure Full Stack Development Artificial Intelligence Business Transformation Event-Driven Programming Service Level Objectives Go (Programming Language) Cloud-Native Applications Java (Programming Language) Amazon Elastic Compute Cloud Healthcare Industry Knowledge Back End (Software Engineering) Troubleshooting (Problem Solving) Object-Oriented Programming (OOP) Application Programming Interface (API) +0

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• 3-5+ years of experience developing perception systems for robotics, autonomous vehicles, or advanced driver/operator assist systems.
• 2+ years with Machine Learning for Perception (tuning and training models/deep learning)
• Strong understanding of computer vision, sensor fusion, and machine learning concepts applied to real-world perception problems.
• Proficiency in C++ and Python for developing production-quality perception and autonomy software.
• Experience with ROS or similar autonomous infrastructure software frameworks for robotic systems.
• Hands-on experience working with camera, lidar, and/or radar data for perception and autonomy applications.
• Practical experience using OpenCV for computer vision tasks and TensorFlow or PyTorch for deep learning-based perception models.
• Experience with mobile robotics perception for autonomy or advanced operator assist systems, including computer vision, machine learning, and deep learning techniques.
• Familiarity with lidar, radar, and cameras as perception sensors and their integration into autonomy software stacks.
• Working knowledge of the Agile software development life cycle and its application to perception and autonomy software projects.

NICE TO HAVE

• Experience using modern development tools such as Git, DockSr. er, CMake, and testing frameworks to build, test, and deploy software.
• Ability to design, write, test, and review autonomy and advanced operator-assist perception software in a collaborative environment.
• Proven ability to work both independently and as part of a multidisciplinary engineering team.
• Ability to solve complex technical issues that span multiple subsystems, including software, sensors, and data processing pipelines.
• Experience with Eigen for numerical and linear algebra operations in perception and autonomy algorithms.
• Familiarity with Azure DevOps or Jira for project management, work item tracking, and Agile collaboration.
• Knowledge of standard software development tools such as SonarQube, GoogleTest, Artifactory, and Clang used in mobile robot perception system development.
• Knowledge of cloud compute and storage tools, including AWS EC2, S3, and Batch, for training, deploying, or scaling perception and machine learning workloads.
• Experience with code development tools and continuous integration/continuous delivery practices for perception software.
• Background in artificial intelligence, autonomy, or advanced operator assist systems is highly beneficial.
• Strong documentation skills for architecture, design, test plans, and operational procedures.
• Comfort working with complex autonomy systems and integrating perception modules into larger machine control frameworks., Individual compensation offered for this position within this range will depend on many factors, including qualifications, skills, relevant experience, job knowledge, geographic location, internal equity, and other pertinent job-related factors., Sensors Research Robotics Debugging Visionary SonarQube Operations Innovation Algorithms TensorFlow Googletest Reliability Artifactory Azure DevOps Test Planning Deep Learning Sensor Fusion Data Pipelines Linear Algebra Data Processing Computer Vision Customer Service Computer Science Machine Learning Object Detection Machine Controls Technical Issues Agile Methodology Software Features Programming Tools Safety Procedures Project Management Amazon Web Services Autonomous Vehicles Continuous Delivery Software Frameworks Software Development Architectural Design Continuous Integration Continuous Development Artificial Intelligence Robot Operating Systems Engineering Design Process Agile Software Development C++ (Programming Language) Software Quality (SQA/SQC) Verification And Validation Hardware Platform Interface Git (Version Control System) Amazon Elastic Compute Cloud Python (Programming Language) Continuous Improvement Process PyTorch (Machine Learning Library) Light Detection And Ranging (LiDAR), DevOps Dashboard Debugging Operations Leadership Kubernetes AWS Lambda Scalability Reliability Communication Microservices Observability Systems Design Problem Solving Fault Tolerance Computer Science

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