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Perception Algorithm Engineer Jobs in Florida (NOW HIRING)

Computer Vision Engineer Sr I

Naples, FL · On-site

$105K - $123.80K/yr

... perception systems. Essential Duties and Responsibilities ... Explore and implement robust computer vision algorithms for different camera models, Multiview ...

Computer Vision Engineer Sr I

Naples, FL

$105K - $123.80K/yr

... perception systems. Essential Duties and Responsibilities ... Explore and implement robust computer vision algorithms for different camera models, Multiview ...

We're seeking a Software Engineering Intern to join our team in Houston, TX or Pensacola, FL and ... Develop algorithms for walking, balance, and bipedal movement control systems * Perception Systems

... perception solutions, with the goal of making mobility and autonomy safer. Our engineering ... Mapping algorithms to FPGA appropriate logic implementations > * Expert integrating and bringing up ...

C., and Hamburg, Germany, enables us to develop and supply integrated lidar hardware and perception ... Mapping algorithms to FPGA appropriate logic implementations > * Expert integrating and bringing up ...

... perception solutions, with the goal of making mobility and autonomy safer. Our engineering ... Mapping algorithms to FPGA appropriate logic implementations * Expert integrating and bringing up ...

C., and Hamburg, Germany, enables us to develop and supply integrated lidar hardware and perception ... Mapping algorithms to FPGA appropriate logic implementations * Expert integrating and bringing up ...

C., and Hamburg, Germany, enables us to develop and supply integrated lidar hardware and perception ... Mapping algorithms to FPGA appropriate logic implementations * Expert integrating and bringing up ...

... perception solutions, with the goal of making mobility and autonomy safer. Our engineering ... Mapping algorithms to FPGA appropriate logic implementations * Expert integrating and bringing up ...

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Perception Algorithm Engineer information

What are the key skills and qualifications needed to thrive as a Perception Algorithm Engineer, and why are they important?

To thrive as a Perception Algorithm Engineer, you need a strong background in computer vision, machine learning, and programming (typically C++ or Python), often supported by a degree in computer science, robotics, or a related field. Familiarity with tools like TensorFlow, PyTorch, OpenCV, and ROS, as well as experience with sensor data (e.g., LiDAR, cameras), is crucial. Strong analytical thinking, problem-solving abilities, and effective teamwork are standout soft skills for this role. These skills are vital to develop robust perception systems that enable autonomous vehicles and robots to interpret and interact safely with complex real-world environments.

What are some common challenges faced by Perception Algorithm Engineers when integrating their solutions into autonomous systems?

Perception Algorithm Engineers often encounter challenges when ensuring their algorithms perform reliably in diverse real-world environments, such as varying lighting, weather conditions, and sensor noise. Integrating algorithms with hardware requires close collaboration with robotics and systems engineering teams to optimize performance and latency. Additionally, balancing accuracy with computational efficiency is crucial, as perception modules must run in real time on embedded systems. Addressing these challenges involves rigorous testing, continuous model improvement, and effective cross-functional communication.

What is a Perception Algorithm Engineer?

A Perception Algorithm Engineer is a professional who develops algorithms that enable machines—such as autonomous vehicles or robots—to interpret and understand sensory data from their environment. This typically involves processing data from cameras, lidar, radar, and other sensors to identify objects, track movement, and understand surroundings. Perception Algorithm Engineers work with computer vision, sensor fusion, and machine learning techniques to create reliable and efficient perception systems. Their work is crucial in making machines aware of their surroundings and enabling them to respond appropriately. They often collaborate with hardware, software, and robotics teams to integrate their algorithms into real-world applications.
What job categories do people searching Perception Algorithm Engineer jobs in Florida look for? The top searched job categories for Perception Algorithm Engineer jobs in Florida are:
What cities in Florida are hiring for Perception Algorithm Engineer jobs? Cities in Florida with the most Perception Algorithm Engineer job openings:

Senior Developer - AI/ML Autonomous Driving & Navigation

Intrepidus Talent Solutions

Melbourne, FL

$113.50K - $149.70K/yr

Full-time

Posted 28 days ago


Job description

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.