Responsibilities:

• Algorithm Development: Develop and optimize computer vision and machine learning algorithms for object detection, classification, tracking, and scene understanding
• Sensor Fusion: Integrate data from a variety of sensors, such as cameras, LiDAR, radar, and GPS, to provide a comprehensive perception system for ASVs
• Real-time Processing: Implement real-time data processing pipelines to ensure rapid and accurate perception feedback to the ASV’s control system
• MLops: Collaborate with data annotation teams to create labeled datasets for training and validation of perception algorithms
• Performance Optimization: Optimize perception algorithms for efficient use of computational resources, ensuring they meet the real-time requirements of autonomous navigation
• Testing and Validation: Conduct extensive testing and validation of perception systems in simulated and real-world maritime environments, identifying and addressing issues as they arise
• Documentation: Maintain comprehensive documentation of perception software, including code, algorithms, and test results
• Collaboration: Work closely with multidisciplinary teams, including hardware engineers, control engineers, and navigation experts, to integrate perception systems into the ASVs
• Stay Current: Keep abreast of the latest advancements in computer vision, sensor technologies, and machine learning to continually improve and adapt perception systems 

Qualifications:

• Proficiency in programming languages such as Python, C++, and CUDA
• Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch)
• Understanding of various filters and their applications
• Basic proficiency in Rust
• Experience with maritime or autonomous vehicle projects is a plus
• Experience with signals processing or sensor fusion is a plus
• Experience with low latency inference and tracking pipelines is a plus