Robotics Autonomy Engineer

Hernshead Recruitment; Boston (MA); On-site; USD 120,000 - 180,000; Full time

Job summary

Hernshead Recruitment seeks an experienced robotics/autonomy engineer to own and advance the autonomy stack for an unconventional UAV platform. Work spans localization, mapping, perception, navigation, and edge compute challenges while collaborating across autonomy, perception, sensors, and flight controls.

Responsibilities include developing SLAM, sensor fusion, real-time optimization, and mission-level behaviors for safe, reliable operation on compute-constrained hardware.

Qualifications

• Bachelor's degree in Robotics, Computer Science, Computer Engineering, or a related field; Master's in Robotics, Autonomous Systems, Controls, or Computer Vision a plus
• 3-5 years developing autonomy, localization, state estimation, navigation, or flight software for robots, UAVs, autonomous vehicles, or similarly complex physical systems
• Proven experience deploying autonomy software on real robotic systems in the field, not just simulation or research
• Strong hands-on experience with visual odometry, VIO, 3D mapping, sensor fusion, and SLAM, including EKF-based estimation, calibration, and time synchronization
• Practical experience with perception, obstacle detection, motion and path planning, trajectory generation/optimization, and map representations such as occupancy grids and octrees
• Deep proficiency in C++ and C, and strong proficiency in Python; embedded systems or flight control software experience highly valuable
• Experience on embedded Linux and SoCs such as Qualcomm Snapdragon or NVIDIA Jetson, including GPU/DSP profiling and optimization for real-time constraints
• Experience with ROS2, Linux, Git, Docker, and modern software practices; deployed fleet/telemetry experience a strong plus
• Strong ownership mentality, able to work independently through ambiguous technical problems from definition to deployment
• Clear technical communication and effective cross-team collaboration
• Bonus: UAV flight stack experience (PX4, ArduPilot, MAVLink, offboard control); Gazebo/Isaac Sim/AirSim sim-to-real experience; experience mentoring engineers or leading a small team

Responsibilities

• Own and advance the autonomy stack spanning localization, mapping, state estimation, sensor fusion, path planning, and obstacle avoidance
• Develop and harden visual-inertial and LiDAR-based SLAM, multi-sensor fusion, sensor calibration, relocalization, drift management, and map persistence
• Build perception and reactive autonomy for obstacle detection, free-space understanding, dynamic replanning, and safe navigation in unpredictable environments
• Develop autonomous behaviors including path following, mission execution, data collection, health monitoring, fault detection, redundancy, graceful degradation, recovery, and safe return
• Profile and optimize C/C++ for real-time performance within strict latency, memory, compute, power, and thermal budgets on embedded edge hardware
• Build and improve simulation, log replay, automated testing, regression benchmarks, telemetry, CI/CD, deployment, and fleet diagnostics
• Own real-world autonomy performance through bench and field testing, flight-log analysis, and root-cause debugging
• Help define the autonomy architecture and roadmap

Skills

Robotics

Autonomy

C/C++

Python

ROS2

Embedded Linux

VIO/SLAM

Education

Bachelor's degree in Robotics/CS/CE

Master's in Robotics/Autonomous Systems/Controls/Comp Vision a plus

Tools

ROS2

Linux

Git

Docker

CUDA/Jetson/SoCs

Job description

This role owns and advances the autonomy stack for an unconventional UAV platform, covering localization, mapping, state estimation, sensor fusion, path planning, and obstacle avoidance. The engineer will work across autonomy, perception, sensors, flight controls, and vehicle dynamics to solve system-level problems, taking cutting-edge robotics research and turning it into reliable capability that runs on compute-constrained edge hardware. The role reports to the CTO and carries significant independence in shaping the autonomy architecture and roadmap.

Job Responsibilities:

• Develop and harden visual-inertial and LiDAR-based SLAM, multi-sensor fusion, sensor calibration, relocalization, drift management, and map persistence
• Build perception and reactive autonomy for obstacle detection, free-space understanding, dynamic replanning, and safe navigation through unpredictable environments
• Build autonomous behaviors including path following, mission execution, data collection, health monitoring, fault detection, redundancy, graceful degradation, recovery, and safe return
• Profile and tune C/C++ for real-time performance within strict latency, memory, compute, power, and thermal budgets on embedded edge hardware
• Build and improve simulation, log replay, automated testing, regression benchmarks, telemetry, CI/CD, deployment, and fleet diagnostics
• Own real-world autonomy performance through bench and field testing, flight-log analysis, and root-cause debugging
• Help define the autonomy architecture and roadmap

Experience Required:

• Bachelor's degree in Robotics, Computer Science, Computer Engineering, or a related field; Master's in Robotics, Autonomous Systems, Controls, or Computer Vision a plus
• 3-5 years developing autonomy, localization, state estimation, navigation, or flight software for robots, UAVs, autonomous vehicles, or similarly complex physical systems
• Proven experience deploying autonomy software on real robotic systems in the field, not just simulation or research
• Strong hands-on experience with visual odometry, VIO, 3D mapping, sensor fusion, and SLAM, including EKF-based estimation, calibration, and time synchronization
• Practical experience with perception, obstacle detection, motion and path planning, trajectory generation/optimization, and map representations such as occupancy grids and octrees
• Deep proficiency in C++ and C, and strong proficiency in Python; embedded systems or flight control software experience highly valuable
• Experience on embedded Linux and SoCs such as Qualcomm Snapdragon or NVIDIA Jetson, including GPU/DSP profiling and optimization for real-time constraints
• Experience with ROS2, Linux, Git, Docker, and modern software practices; deployed fleet/telemetry experience a strong plus
• Strong ownership mentality, able to work independently through ambiguous technical problems from definition to deployment
• Clear technical communication and effective cross-team collaboration
• Bonus: UAV flight stack experience (PX4, ArduPilot, MAVLink, offboard control); Gazebo/Isaac Sim/AirSim sim-to-real experience; experience mentoring engineers or leading a small team