About Us
At Agtonomy, we’re not just building tech—we’re transforming how vital industries get work done. Our Physical AI and fleet services turn heavy machinery into intelligent, autonomous systems that tackle the toughest challenges in agriculture, turf, and beyond. Partnering with industry-leading equipment manufacturers, we’re creating a future where labor shortages, environmental strain, and inefficiencies are relics of the past. Our team is a tight-knit group of bold thinkers—engineers, innovators, and industry experts—who thrive on turning audacious ideas into reality. If you want to shape the future of industries that matter, this is your shot.
About the Role
You will be responsible for developing state estimation and localization 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
Implementing new features to improve the stability and reliability of our local and global pose estimates.Designing mitigation and fallback strategies for the pose estimation systems.Researching, prototyping, and experimenting with various sensors and state-of-the-art state estimation algorithms.Architecting, designing, and implementing software applications, as well as onboard and offboard infrastructure and tools to support those applications.Developing portable, scalable, and fast state measurement and optimization libraries.Writing performant, well-tested software, and improving code quality of the entire Autonomy team through code and design reviews.Validating 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.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 (gives “field testing” a whole new meaning!).
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.Thinks/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
• 401k Plan
• Stock Options
• Collaborative work environment working alongside passionate mission-driven team!
Our interview process is generally conducted in five (5) phases:
1. Phone Screen with Hiring Manager (30 minutes)
2. Technical Evaluation in Domain (1 hour)
3. Software Engineering Evaluation (1 hour)
4. Panel Interview (Video interviews scheduled with key stakeholders, each interview will be 30 to 60 minutes)
