Intern
Moss
Intern
Moss
Autonomous field robots digitizing outdoor forests
At moss.inc, we are making the physical world searchable. Our sensor kits mount to vehicles our customers already drive, and turn every drive into a measured 3D record of their site, across agriculture, construction, and energy. Our AI models then parse through those 3D maps and decipher important information for each of our customers. We started with tree farms, where a single field holds millions of plants no human has ever fully inventoried. 🌲🤯🌳
We're a small team of practical engineers with a long-term vision. We focus on real, messy, on-the-ground problems today, while working toward a future where AI agents understand the physical world.
If our mission aligns with how you work and think, we'd love to learn more about you.
Join us as an ML, Perception, or Robotics Intern on a fast-moving team building the systems that allow our robots to understand and operate in complex outdoor environments.
Depending on your interests and experience, you may work on 3D perception, multimodal ML, sensor fusion, mapping, localization, navigation, or autonomy.
You might train detection and segmentation models on large custom datasets, fuse LiDAR and camera data, build 3D mapping and localization systems, develop robot behaviors, or optimize models and algorithms for real-time deployment on edge GPUs.
Our robots operate through changing light, harsh shadows, motion, dust, dense vegetation, uneven terrain, and severe occlusions. You’ll work across the full loop — from data and research to deployment, field failures, and iteration on real robots.
We’re hiring for Spring 2027 internships, co-ops, and part-time roles, with the possibility of starting earlier part-time.
Impressive technical projects beyond the classroom in ML, computer vision, perception, robotics, mapping, or related fields
Strong programming skills in Python, C++, or Rust
Hands-on experience with at least one of the following:
Machine learning or computer vision
3D perception, point clouds, or sensor fusion
Localization, mapping, navigation, controls, or robot behaviors
Comfortable working in Linux and debugging real systems
Excited to learn quickly, take ownership, and test your work on real robots
Experience with PyTorch, LiDAR, cameras, ROS, CUDA, model deployment, or edge computing is valuable but not required
Own projects from research and design through deployment and iteration on real robots
Build and evaluate ML, perception, mapping, and autonomy systems
Train models on custom outdoor datasets collected by our robots
Develop sensor fusion across LiDAR, cameras, GPS/IMU, and other sensors
Build localization, navigation, controls, and robot behaviors
Develop tools for data collection, labeling, training, evaluation, simulation, and field debugging
Optimize models and algorithms for latency, memory usage, and reliability on edge hardware
Test and deploy robotic systems during real-world customer operations
Collaborate closely with perception, software, electrical, and mechanical engineers
Moss builds autonomous field robots to digitize the outdoor world, starting with tree farms where millions of plants are hard to count. The robots move through harsh outdoor environments to map and inventory plants, collecting data that makes the physical world searchable. The product works by deploying mobile robots with sensors to traverse fields, capture imagery and measurements, and compile it into a searchable digital inventory. Moss differentiates itself by tackling real, messy on-the-ground problems with a small, practical engineering team and a long-term plan to expand to other outdoor tasks, not just software. The goal is to make dangerous outdoor jobs safer and easier by using autonomous robots that can operate where humans won't.
Explore more opportunities at Moss