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Map Localization Jobs in Florida (NOW HIRING)

Map Localization information

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

To thrive as a Map Localization Engineer, you need a strong background in robotics, computer vision, and algorithms, often supported by a degree in computer science, electrical engineering, or a related field. Proficiency with tools and frameworks such as ROS (Robot Operating System), SLAM (Simultaneous Localization and Mapping), and programming languages like C++ and Python is typically required. Strong problem-solving skills, attention to detail, and effective communication are essential soft skills for collaborating on complex projects and debugging localization systems. These skills are crucial for developing accurate and reliable localization solutions that enable autonomous navigation and mapping in real-world environments.

What are some common challenges faced by professionals working in map localization roles?

Professionals in map localization often encounter challenges such as managing the accuracy of real-time data from multiple sources and ensuring that maps remain up-to-date with constantly changing environments. Additionally, working with large volumes of geospatial data requires strong analytical and technical skills, especially when integrating information from LiDAR, GPS, and camera systems. Collaboration with cross-functional teams, such as software developers and robotics engineers, is essential to solve localization issues and to deliver reliable navigation solutions. Staying current with advances in localization algorithms and mapping technologies is also important for ongoing success in this field.

What is map localization?

Map localization is the process of determining a device's or vehicle’s precise position within a known map or environment. It is a crucial component in robotics, autonomous vehicles, and navigation systems, allowing them to understand their location relative to their surroundings. Accurate map localization enables systems to navigate safely, avoid obstacles, and perform tasks efficiently. This process often uses sensors like GPS, LiDAR, cameras, and algorithms such as SLAM (Simultaneous Localization and Mapping).

What is the difference between Map Localization vs GIS Technician?

AspectMap LocalizationGIS Technician
Required CredentialsGPS, GIS, or mapping software certificationsGIS certifications, degree in geography or related field
Work EnvironmentFieldwork, outdoor mapping, mobile devicesOffice-based, desktop GIS software
Employer & Industry UsageNavigation apps, autonomous vehicles, outdoor mappingUrban planning, environmental management, utilities
Search & Comparison IntentUnderstanding field mapping rolesTechnical GIS data management

Map Localization focuses on real-time positioning and navigation, often in outdoor or mobile environments, using GPS and mapping tools. GIS Technicians handle spatial data analysis, map creation, and GIS software management primarily in office settings. While both roles involve geographic data, Map Localization emphasizes field-based positioning, whereas GIS Technicians focus on data processing and map development.

What are popular job titles related to Map Localization jobs in Florida? For Map Localization jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Map Localization jobs in Florida look for? The top searched job categories for Map Localization jobs in Florida are:
What cities in Florida are hiring for Map Localization jobs? Cities in Florida with the most Map Localization job openings:
Infographic showing various Map Localization job openings in Florida as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution.

Senior Developer - AI/ML Autonomous Driving & Navigation

Intrepidus Talent Solutions

Melbourne, FL

$113.50K - $149.70K/yr

Full-time

Posted 27 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.