Senior Developer – AI/ML Autonomous Driving & Navigation

Intrepidus Talent Solutions

Senior Developer – AI/ML Autonomous Driving & Navigation

Melbourne, FL
Full Time
Paid
  • Responsibilities

    Senior Developer – AI/ML Autonomous Driving & Navigation

    Location: Onsite Employment Type: Full-Time

    About the Opportunity

    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.

     

    Position Summary

    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.

    Key Responsibilities

    • 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.

    Required Qualifications

    • 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, TensorFlow, 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.

    Preferred Qualifications

    • 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 safety-critical software development.
    • Experience with Kalman filters, probabilistic estimation, occupancy grids, route planning, and mission planning.
    • Experience with synthetic data, digital twins, or simulation environments (CARLA, Gazebo, AirSim, or similar).
    • Familiarity with safety, verification, and validation standards or processes.
    • Experience leading small technical teams or owning major autonomy subsystems.

     

    Technical Skills

    • Languages: C++, Python
    • Frameworks/Libraries: PyTorch, TensorFlow, OpenCV, ROS/ROS2
    • Core Concepts: Machine Learning, Deep Learning, Sensor Fusion, SLAM, Path Planning, Computer Vision, Navigation, Localization
    • Tools: Linux, Git, Docker, CI/CD, simulation and test frameworks
    • Nice to Have: CUDA, embedded GPU platforms, real-time systems, cloud-based model training pipelines

    Leadership & Behavioral Competencies

    • Strong ownership and accountability.
    • Ability to balance research innovation with product delivery.
    • Excellent written and verbal communication skills.
    • Strong collaboration across software, systems, hardware, and test teams.
    • Technical leadership and mentoring capability.
    • Ability to decompose complex autonomy challenges into executable development plans.

    What Success Looks Like

    • Delivering reliable autonomy software that performs in both simulation and field environments.
    • Improving perception, navigation, and decision-making accuracy and robustness.
    • Reducing integration risk through disciplined software architecture and testing.
    • Helping mature AI/ML autonomy capability from concept to deployable product.
    • Serving as a senior technical contributor and trusted leader within the autonomy team.