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Software Engineer, Odometry & Localization

Job in Emeryville, Alameda County, California, 94608, USA
Listing for: Agtonomy
Full Time position
Listed on 2026-06-14
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Software Engineer, Robotics, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 170000 - 240000 USD Yearly USD 170000.00 240000.00 YEAR
Job Description & How to Apply Below

About The Role

You will be responsible for developing state estimation algorithms to help our vehicles more accurately estimate their pose with respect to the local and global frames. You will work closely with perception, planning, and controls engineers on the team to design and evolve the outputs of the pose and localization systems to better serve their consumers. This role is perfect for someone who loves combining math and software, and is excited about applying their experience to make robots drive in smart ways in rugged, agricultural environments.

What

you'll do
  • Implement new features to improve the stability and reliability of our local and global pose estimates
  • Design mitigation and fallback strategies for the pose estimation systems
  • Research, prototype, and experiment with various sensors and state-of-the-art state estimation algorithms
  • Architect, design, and implement software applications, as well as onboard and offboard infrastructure and tools to support those applications
  • Develop portable, scalable, and fast state measurement and optimization libraries
  • Write performant, well‑tested software, and improve code quality of the entire Autonomy team through code and design reviews
  • Validate your solutions on real vehicles in real‑world scenarios
What you'll bring
  • Demonstrated experience deploying state estimation algorithms in real robots:
    Factor graphs, Kalman filters, particle filters, structure from motion, visual inertial odometry, lidar odometry, etc.
  • Deep understanding of the design tradeoffs involved when fusing various sensing technologies: cameras (mono and stereo), LiDAR, RADAR, GNSS, IMUs, wheel encoders, etc.
  • Experience implementing state estimation math effectively in software with the following libraries:
    Eigen, Sophus, Ceres, GTSAM, etc.
  • Strong proficiency in modern C++ and experience writing efficient algorithms for resource‑constrained embedded systems. This is a required skill for the position.
  • Ability to thrive in a fast‑moving, collaborative, small team environment with lots of ownership.
  • Excellent analytical, communication, and documentation skills with demonstrated ability to collaborate with interdisciplinary stakeholders outside of Autonomy.
  • An eagerness to get your hands dirty by testing your code on real robots at real customer farms.
What Makes You a Strong Fit
  • Experience architecting state estimation systems from scratch and understanding the design tradeoffs when leveraging filters, pose graph optimization, etc.
  • Experience implementing custom factors for factor graph optimization.
  • Experience with state‑of‑the‑art visual odometry and/or lidar odometry algorithms.
  • Built SLAM solutions from scratch, not just tuned open‑source ones.
  • Think/dreams in Lie algebra.
  • 5+ years of software development experience in autonomy, robotics, or a related field.
  • MS or PhD in Robotics, Computer Science, Computer Engineering, Electrical Engineering, or a related field.
Benefits
  • 100% covered medical, dental, and vision for the employee (partner, children, or family is additional).
  • Commuter Benefits.
  • Flexible Spending Account (FSA).
  • Life Insurance.
  • Short‑ and Long‑Term Disability.
  • 401(k) Plan.
  • Stock Options.
  • Collaborative work environment working alongside passionate mission‑driven team!

The US base salary range for this full‑time position is $170,000 to $240,000 + equity + benefits + unlimited PTO. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location, internal equity, and additional factors, including, but not limited to, job‑related skills, experience, and relevant education or specialty training.

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