Key Responsibilities and Required Skills for Unmanned Vehicle Engineer

🎯 Role Definition

The Unmanned Vehicle Engineer is a hands-on systems and software engineer responsible for designing, integrating, testing and fielding autonomous vehicle platforms (UAVs, UGVs, USVs). This role leads vehicle autonomy development across perception, navigation, control, sensor fusion and embedded systems, driving mission performance, safety, and regulatory compliance while collaborating with hardware, software, test, and operations teams.

📈 Career Progression

Typical Career Path

Entry Point From:

Junior Robotics Engineer / Embedded Software Engineer
Test Engineer (autonomy / avionics)
Systems Integration Engineer (mechatronics, controls)

Advancement To:

Senior/Lead Unmanned Vehicle Engineer
Autonomy Systems Lead / Principal Engineer
Engineering Manager (Autonomy or Vehicle Programs)

Lateral Moves:

Perception / Computer Vision Engineer
Flight Controls / Guidance, Navigation & Control (GNC) Engineer

Core Responsibilities

Primary Functions

Lead the architecture, design and implementation of autonomous vehicle systems, including perception, state estimation, navigation, guidance and control, ensuring modularity, scalability and real-time performance.
Develop, implement, and optimize sensor fusion algorithms (INS/GNSS, LiDAR, Radar, camera) and Kalman filters to provide robust vehicle state estimation in GPS-denied and degraded environments.
Design and implement SLAM and mapping solutions for 2D/3D environment representation and real-time localization across UAV/UGV/USV platforms using ROS/ROS2 or equivalent middleware.
Author, maintain and extend vehicle autonomy software in C++, Python and embedded C, ensuring efficient use of CPU, GPU and microcontroller resources on constrained platforms.
Integrate and validate perception pipelines (computer vision, object detection, segmentation, tracking) using frameworks such as OpenCV, TensorFlow, PyTorch and on-device inference engines.
Define systems requirements and translate high-level mission requirements into hardware and software specifications, interface control documents, and testable acceptance criteria.
Perform hardware-software integration: select and integrate sensors (LiDAR, cameras, IMUs, radars), communication modules (CAN, Ethernet, RF, satellite), actuators and power systems; develop drivers and board support packages as needed.
Lead model-based design and simulation activities using MATLAB/Simulink, Gazebo, Carla, or custom simulators to validate algorithms and mission scenarios prior to field testing.
Implement and execute verification & validation (V&V) plans, unit/integration/system tests, and automated test benches including hardware-in-the-loop (HIL) and software-in-the-loop (SIL) testing.
Plan and conduct field tests, collect flight/drive logs, analyze telemetry, and iterate designs based on empirical performance and reliability data.
Develop and maintain CI/CD pipelines, automated regression tests, and code review standards to support rapid, safe development and deployment of autonomy software.
Troubleshoot and perform root-cause analysis for in-field anomalies; propose corrective design changes, firmware updates, or test regimen improvements.
Ensure functional safety and system assurance by applying standards and methods (e.g., ISO 26262 concepts, DO-178C awareness, SOTIF practices) to autonomy features and mission-critical subsystems.
Drive performance tuning and resource management for real-time control loops, perception pipelines, and embedded middleware to meet latency and determinism requirements.
Collaborate with mechanical and electrical engineering teams to refine vehicle platforms for manufacturability, maintainability and mission endurance (thermal, vibration, EMI/EMC considerations).
Produce and maintain clear technical documentation — requirements, interface control documents, test plans, FMEAs, and release notes — to support cross-functional teams and customers.
Coordinate with suppliers and manufacturing partners for procurement, qualification and integration of COTS and custom hardware, including executing acceptance tests and resolving nonconformances.
Work with cybersecurity teams to implement secure boot, authenticated updates, encryption and network hardening for vehicle communication and mission data.
Support mission planning and operations teams by integrating mission logic, failsafe behaviors, remote control modes and health monitoring systems into the vehicle stack.
Mentor junior engineers, provide technical direction in design reviews, and lead cross-disciplinary problem-solving sessions to accelerate team capability.
Drive continuous improvement initiatives: reduce weight, increase endurance, lower cost-of-ownership, and improve reliability through iterative design and field feedback loops.
Support proposal capture and technical sales by preparing technical sections, capability demonstrations and risk assessments for new unmanned systems contracts.
Maintain awareness of regulatory, airspace/maritime/land-use rules and help ensure platform compliance with local and international requirements for unmanned operations.
Plan and execute calibration, diagnostic and maintenance procedures, and develop tools for quick field reconfiguration and data collection.

Secondary Functions

Support customer integration, deployment and post-deployment technical support for unmanned vehicle systems and autonomy releases.
Contribute to the organization’s technical roadmap by identifying emerging sensors, compute architectures and autonomy paradigms that improve mission capability.
Participate in trade shows, conferences and technical working groups to represent the company and stay current with industry best practices in autonomy and robotics.
Provide training materials and workshops for operations, maintenance and test personnel on safe use and troubleshooting of autonomous systems.
Assist business development by estimating technical effort, risks, and cost drivers for proposals and SOWs related to unmanned vehicle programs.
Evaluate third-party algorithms, middleware and cloud services for fit, performance and integration risk, and manage vendor relationships.
Help define component obsolescence strategies and lifecycle plans for long-term fleet sustainment and update paths.
Drive post-mortem analysis and lessons-learned sessions following complex test campaigns, ensuring knowledge capture and process improvements.

Required Skills & Competencies

Hard Skills (Technical)

Proficient in C++ and Python for autonomy and embedded development; experience with modern C++ standards and memory-safe practices.
Hands-on experience with ROS/ROS2, nav stack, action servers, topics, services and custom node development for vehicle autonomy.
Expertise in sensor fusion and state estimation (EKF/UKF, particle filters), GNSS/INS integration, and handling of degraded navigation scenarios.
Strong background in perception: computer vision, point-cloud processing (PCL), LiDAR/Radar data processing, object detection and tracking.
Experience with SLAM, mapping, and localization techniques for large-scale and GPS-challenged environments.
Embedded systems development experience on RTOS (FreeRTOS, VxWorks) and working knowledge of microcontrollers (ARM Cortex), SoCs and heterogeneous compute (CPU+GPU/TPU).
Model-based design and simulation skills using MATLAB/Simulink, Gazebo, Carla, or similar environments; ability to derive test cases from requirements.
Familiarity with control theory and implementation of guidance, navigation and control algorithms (PID, LQR, MPC) for stable and responsive vehicle behavior.
Knowledge of networking and communications: CAN, Ethernet, ROS bridges, RF modems, LTE/5G, satellite communications; understanding of latency and reliability trade-offs.
Experience with hardware-in-the-loop (HIL), software-in-the-loop (SIL) testing frameworks, automated test harnesses and telemetry logging systems.
Proficient with version control (Git), CI/CD tools (Jenkins/GitLab CI), and automated build/test pipelines for multi-platform deployment.
Competence in performance profiling, real-time optimization, and low-level debugging tools (gdb, valgrind, perf) for both embedded and application-level code.
Familiarity with safety, security and quality standards applicable to unmanned systems (ISO 26262 concepts, DO-178C awareness, MIL-STD, cybersecurity best practices).
Experience with machine learning model deployment on edge devices and optimizing models for inference (quantization, pruning, ONNX).
Practical experience integrating and validating sensors and COTS hardware, including calibration procedures, sensor alignment and environmental testing.
Knowledge of manufacturing and sustainment concerns: DFMEA, test fixtures, calibration jigs and maintainability engineering.
Experience with cloud tooling and data pipelines for mission data ingestion, replay and offline analysis (AWS/GCP/Azure optional).
Proficiency with technical documentation tools and the ability to produce formal engineering documentation, test reports and release notes.
Demonstrated ability to perform root cause analysis and corrective actions following component failures or system-level anomalies.
Experience with simulation-to-real transfer strategies and methods to reduce sim-to-real gaps for autonomous behaviors.

Soft Skills

Strong written and verbal communication skills for cross-functional collaboration with hardware, software, operations and customers.
Systems-thinking and the ability to balance trade-offs across performance, weight, power, cost and schedule.
Proven problem-solving skills and comfort with ambiguity in early-stage vehicle development and test campaigns.
Attention to detail, discipline around testing procedures and quality assurance to manage safety-critical functionality.
Leadership and mentoring aptitude; ability to grow junior engineers and lead technical design reviews.
Time management and prioritization skills to handle parallel development, integration and field test tasks.
Collaborative mindset with experience working in agile or hybrid development processes.
Customer-facing orientation with the ability to translate technical detail into operational impact and risk mitigation.
Adaptability to field conditions, travel to test sites and iterative development cycles.
Initiative and ownership: accountable for features from requirements through deployment and sustainment.

Education & Experience

Educational Background

Minimum Education:

Bachelor’s degree in Aerospace Engineering, Mechanical Engineering, Electrical/Electronics Engineering, Computer Science, Robotics, or related STEM field.

Preferred Education:

Master’s or PhD in Robotics, Controls, Aerospace, Computer Vision, or a closely related discipline.

Relevant Fields of Study:

Aerospace Engineering
Robotics / Mechatronics
Electrical or Electronic Engineering
Mechanical Engineering
Computer Science / Software Engineering
Control Systems / Applied Mathematics

Experience Requirements

Typical Experience Range: 3–8 years of hands-on experience in autonomy, robotics, embedded systems or avionics, with demonstrable experience on unmanned platforms.

Preferred:

5+ years experience specifically developing, integrating and testing autonomy stacks on UAVs, UGVs or USVs.
Demonstrated field test leadership on multi-sensor platforms and a portfolio of mission deployments, logged data analysis and performance improvements.
Prior work with ROS/ROS2, SLAM, sensor fusion, and embedded real-time systems combined with productionizing autonomy features for customers.