Spring ’27 Intern – ML / Perception / Robotics
San Francisco
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingYou’ll work across the full loop — from data and research to deployment, field failures, and iteration on real robots.
Own projects from research and design through deployment and iteration on real robots
Develop sensor fusion across LiDAR, cameras, GPS/IMU, and other sensors
From the employer’s posting
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.
What You'll Do 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
What you’ll bring
All qualificationsCore experience
- Hands-on experience with at least one of the following:- Machine learning or computer vision
Preferred experience
- Experience with PyTorch, LiDAR, cameras, ROS, CUDA, model deployment, or edge computing is valuable but not required
Qualification wording
Hands-on experience with at least one of the following:- Machine learning or computer vision
Experience with PyTorch, LiDAR, cameras, ROS, CUDA, model deployment, or edge computing is valuable but not required
Tools in this posting
- Python
- PyTorch
- C++
- Rust
Source — Tool mentions in context
- 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
- 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 What You'll Do
About Moss-Ag
At moss.ag, we build robots to go where humans won't, digitizing the physical outdoor world to make it machine-readable.
In the employer’s words · Read in context
Job description
About Us
At moss.ag, we build robots to go where humans won't, digitizing the physical outdoor world to make it machine-readable. Starting 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 autonomous field robots make harsh outdoor jobs easier and safer.
If our mission aligns with how you work and think, we’d love to learn more about you!
The Role
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.
Minimum Requirements
- 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
What You'll Do
- 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
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the salary range before committing time to the process.
Complete your application on jobs.gem.com. The employer’s form will show what is required.
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Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
San Francisco
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- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Sep 9, 2026
- Recorded sightings
- 11
- Last seen by us
- Oct 9, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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