Senior Developer AIML Autonomous Driving Navigation

Senior Developer – AI/ML Autonomous Driving & Navigation

Location: Onsite Employment Type: Full-Time

Our client is a cutting‑edge defense and maritime technology company operating at the forefront of autonomous surface vessel development. They are seeking an experienced Senior Developer to join their software team and build out a suite of autonomy and control software for Unmanned Surface Vessels (USVs). The platform encompasses onboard vessel control components, ground‑based user stations, and network‑distributed components — all pushing the boundary of autonomous maritime navigation.

This role focuses on machine learning, perception, navigation, path planning, sensor fusion, and real‑time decision‑making for autonomous platforms operating in dynamic environments.

The ideal candidate brings strong experience in AI/ML‑based autonomy, robotics software, and maritime navigation systems — including COLREGs implementation and Contact Avoidance Behaviors — with the ability to move from algorithm design through deployment on embedded or real‑time platforms. You will work across perception, controls, systems, simulation, and platform engineering teams to deliver robust, production‑quality autonomous capability.

• Design and develop software for autonomous navigation, including localization, mapping, perception, path planning, obstacle avoidance, and motion decision logic.
• Build and optimize AI/ML models for object detection, classification, tracking, scene understanding, and behavior prediction.
• Develop and integrate sensor fusion solutions using data from cameras, LiDAR, radar, GPS, IMU, and other onboard sensors.
• Implement navigation and autonomy algorithms for structured and unstructured environments.
• Collaborate with systems, controls, and platform teams to integrate autonomy functions into vehicle software architecture.
• Develop software in C++ for real‑time or near‑real‑time autonomy applications.
• Create simulation and test pipelines for model training, algorithm validation, and system verification.
• Support field testing, debug performance issues, and refine autonomy behavior based on real‑world results.
• Improve software reliability, safety, performance, and maintainability using sound engineering practices.
• Contribute to requirements definition, technical planning, architecture reviews, and code reviews.
• Mentor junior engineers and provide technical leadership in AI/ML and autonomy development.
• Support transition from prototype algorithms to production‑ready implementations.

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, Aerospace Engineering, or related field.
• 7+ years of software development experience with significant work in AI/ML, robotics, autonomous systems, or navigation.
• Strong programming skills in C++.
• Knowledge of AI/LLM training and deployment.
• Experience with ML frameworks (PyTorch, Tensor Flow, or equivalent).
• Experience developing perception or navigation algorithms for autonomous systems.
• Strong understanding of one or more of the following areas:
  • Sensor fusion
  • SLAM / localization / mapping
  • Path planning / trajectory generation
  • Computer vision
  • Object tracking
  • Reinforcement learning or behavior planning
• Experience with robotics middleware or autonomy frameworks such as ROS/ROS2 or equivalent.
• Experience with message bus and microservice‑based architectures.
• Hands‑on experience with real‑world sensor data from LiDAR, radar, cameras, GPS, and IMU.
• Familiarity with simulation tools and data analysis workflows.
• Proficiency in Linux‑based development environments, Git, CI/CD, and modern software engineering practices.
• Strong debugging, problem‑solving, and system integration skills.
• Ability to work effectively in cross‑functional teams.

• Strong Python coding skills.
• Master's or Ph.D. in a relevant field.
• Experience with autonomous driving, ADAS, mobile robotics, marine autonomy, UAV autonomy, or other safety‑critical autonomous platforms.
• Experience deploying AI/ML models to embedded, edge, or GPU‑accelerated systems.
• Knowledge of real‑time operating systems or…