I

Senior Robotics Software Engineer - Localization

innoforge • United State
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AI Summary

Own localization and state estimation for a planetary surface vehicle in a GPS-denied outdoor environment. Fuse IMU, camera, LiDAR, and wheel odometry data; deploy algorithms on real hardware and test in realistic terrain. Requires strong C++/Python, SLAM/state estimation expertise, and field testing experience.

Key Highlights
Own the vehicle's localization and state-estimation architecture
Fuse data from IMUs, cameras, LiDAR, wheel odometry and other navigation sensors
Develop and evaluate GPS-denied localization approaches and test on real robotic vehicles
Key Responsibilities
Own the vehicle's localization and state-estimation architecture
Fuse data from IMUs, cameras, LiDAR, wheel odometry and other navigation sensors
Develop and evaluate GPS-denied localization approaches
Test software on real robotic vehicles and in simulation
Measure accuracy, identify failure modes and improve robustness
Integrate localization with planning, autonomy and hazard-avoidance systems
Participate directly in outdoor vehicle testing
Technical Skills Required
C++ Python Sensor fusion
Benefits & Perks
Competitive salary
Equity
Relocation support
Nice to Have
Previous space experience
Experience with outdoor robots, drones, autonomous vehicles, defence autonomy or natural-terrain navigation

Job Description


Senior Robotics Software Engineer - Localization


Hawthorne | On-site | Competitive salary, equity and relocation support


An early-stage space robotics company is hiring a Senior Robotics Software Engineer to own localization and state estimation for a planetary surface vehicle.


The challenge is straightforward to describe but difficult to solve: enable a mobile robot to understand its position reliably in an outdoor, unstructured environment without depending on GPS or prepared infrastructure.


This position combines advanced robotics algorithms with practical engineering on real hardware. The successful engineer will choose the technical approach, implement it, deploy it to the vehicle, test it in realistic terrain, evaluate its limitations and iterate quickly.


The role

  • Own the vehicle’s localization and state-estimation architecture.
  • Fuse data from IMUs, cameras, LiDAR, wheel odometry and other navigation sensors.
  • Develop and evaluate GPS-denied localization approaches.
  • Test software on real robotic vehicles and in simulation.
  • Measure accuracy, identify failure modes and improve robustness.
  • Integrate localization with planning, autonomy and hazard-avoidance systems.
  • Participate directly in outdoor vehicle testing.


Essential experience

  • Localization, SLAM, state estimation or sensor-fusion expertise.
  • Deployment of algorithms onto real robots or autonomous vehicles.
  • Strong C++ and/or Python.
  • Experience with techniques such as EKFs, factor graphs, INS, visual odometry or LiDAR odometry.
  • Ability to move between mathematical analysis, software implementation and field testing.


Experience with outdoor robots, drones, autonomous vehicles, defence autonomy or natural-terrain navigation is particularly relevant.


Previous space experience is useful but not required.


This role will not suit someone whose experience is entirely academic or simulation-based. The company needs an engineer who enjoys getting software working reliably on real hardware.


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