Senior Machine Learning Engineer - LocalizationAutonomous Vehicles | Remote (US or Canada) $187,000 - $250,000 base + bonus + equity What you'll do - Design, train and deploy production ML models for learned localization, odometry, pose estimation, sensor calibration and map matching
- Build scalable training and evaluation pipelines in PyTorch on large real-world datasets
- Improve state estimation and multi-sensor fusion algorithms
- Analyze large-scale data to find failure modes and drive improvements
- Write production code in Python and C++
- Own features end to end and lead design discussions
What we're looking for - Hands-on experience developing your own ML models for localization problems, including architecture, training, loss functions and experimentation
- Experience with learned localization, odometry, pose or state estimation, calibration or map matching
- Strong PyTorch and Python skills
- A solid grounding in 3D geometry, coordinate transforms and probabilistic estimation
- Experience taking models into production
- An MS with 3+ years of relevant experience, a PhD with 1+ year, or equivalent
Nice to have - Traditional localization experience such as SLAM, visual odometry, factor graphs or Kalman filtering, alongside modern ML
- C++
- Distributed training, real-time deployment or uncertainty-aware ML
Backgrounds welcome Automotive, robotics, aerospace, drones, industrial robotics and mobile localization are all welcome. Strong PhDs with applied research are encouraged to apply.
Why join - Build the core localization models for a Level 4 system heading into commercial deployment
- Develop your own models, not off-the-shelf solutions
- Work with large-scale real-world sensor data
- Fully remote, with visa sponsorship available
