C
Physical AI Engineer
Civ Robotics
5 hours ago
Full-time
On-site
San Francisco, California, United States
Physical AI Engineer
San Francisco
Engineering
In office
Full-time
About the Company Civ Robotics is on a mission to automate repetitive tasks within the $3 trillion infrastructure construction industry. We’re dedicated to bridging the workforce gap and accelerating the development of essential infrastructure projects. At the core of our mission is our innovative technology in robotics and autonomous navigation.
With over 100 robots deployed and operating across construction sites worldwide, we pride ourselves in ushering in the next generation of construction layout tools for solar, civil, land surveying, road striping, and general contracting. Our technology is engineered from the ground up to make our customers’ projects more precise, simple, and efficient than ever before.
Join us and become an integral member of our dynamic team, leading the charge in pioneering construction robotics innovation!
About the Role You’ll explore, prototype, and deploy new approaches to intelligence on real robots.
That could mean:
Building learning-based perception and vision systems for unstructured outdoor environments
Exploring
Vision-Language-Action models, foundation models, imitation learning, reinforcement learning, and learned world models
Creating ways for robots to learn from demonstrations, operators, previous missions, and fleet data
Combining classical robotics with modern machine learning rather than treating them as competing philosophies
Developing models for scene understanding, terrain understanding, object detection, segmentation, localization, manipulation, and autonomous behavior
Finding ways to turn large amounts of robot sensor data into useful training data
Building data collection, evaluation, replay, and training pipelines for physical AI
Taking recent research and figuring out what actually works on a robot
Designing experiments, testing them in simulation, and then getting outside and putting them on a machine
Working closely with autonomy, controls, embedded, mechanical, and product engineers
Helping define the longer-term Physical AI architecture for our robots and fleet
At Staff level, you’ll also help identify
what we should be working on next
- not just execute an existing roadmap.
What we're looking for You have deep experience in some combination of:
Machine learning / deep learning
Computer vision
Robotics and autonomous systems
C++ and Python
PyTorch or similar ML frameworks
ROS / ROS2
Real-world sensor data: cameras, LiDAR, GNSS, IMU, or similar
Training, evaluating, and deploying models on real systems
But more importantly, you know how to
make things work outside the lab .
You understand that a model running once in a notebook is very different from a model running every day on a robot.
You care about latency, compute, bad sensors, weird edge cases, changing environments, debugging, and the thousand small details between a good idea and a working machine.
You might be a great fit if
You read new robotics and AI papers and immediately want to try them.
You have side projects involving robots, cameras, drones, arms, cars, embedded systems, or strange pieces of hardware you probably didn’t need to buy.
You enjoy moving between research code and a robot with a wrench next to it.
You’re comfortable questioning the current approach and saying,
There might be a completely different way to solve this.
You don’t divide the world into AI people and robotics people.
And when something finally works on a 10,000-pound machine in the real world, that feels considerably more exciting than improving a benchmark by another 1%.
Bonus points Experience with any of the following is useful, but not required:
Vision-Language Models / Vision-Language-Action models
Imitation learning or reinforcement learning
Robot foundation models
3D perception
Neural rendering / NeRF / Gaussian Splatting
Self-supervised or unsupervised learning
Synthetic data and simulation
NVIDIA Jetson / TensorRT / edge inference
Isaac Sim or other robotics simulators
Large-scale robotics datasets
Learning from teleoperation or human demonstrations
Heavy equipment, autonomous vehicles, agricultural robots, mining, construction, or other outdoor robotics
Why Civ Robotics We have something that is still rare in Physical AI:
Real robots, doing real work, generating real data.
Our machines are deployed in environments where autonomy creates immediate economic value. That gives us the opportunity to close the loop between deployment, data, learning, and improvement.
You’ll be able to build something, put it on a robot, test it in the field, learn from it, and make the next version better.
We’re looking for someone who wants to help figure out what the next generation of real-world robots should look like and then build it.
Benefits & Perks
Comprehensive healthcare coverage (medical, dental, vision) for you and your family.
Competitive salary with growth potential.
Equity options in a fast-growing robotics company.
#J-18808-Ljbffr
San Francisco
Engineering
In office
Full-time
About the Company Civ Robotics is on a mission to automate repetitive tasks within the $3 trillion infrastructure construction industry. We’re dedicated to bridging the workforce gap and accelerating the development of essential infrastructure projects. At the core of our mission is our innovative technology in robotics and autonomous navigation.
With over 100 robots deployed and operating across construction sites worldwide, we pride ourselves in ushering in the next generation of construction layout tools for solar, civil, land surveying, road striping, and general contracting. Our technology is engineered from the ground up to make our customers’ projects more precise, simple, and efficient than ever before.
Join us and become an integral member of our dynamic team, leading the charge in pioneering construction robotics innovation!
About the Role You’ll explore, prototype, and deploy new approaches to intelligence on real robots.
That could mean:
Building learning-based perception and vision systems for unstructured outdoor environments
Exploring
Vision-Language-Action models, foundation models, imitation learning, reinforcement learning, and learned world models
Creating ways for robots to learn from demonstrations, operators, previous missions, and fleet data
Combining classical robotics with modern machine learning rather than treating them as competing philosophies
Developing models for scene understanding, terrain understanding, object detection, segmentation, localization, manipulation, and autonomous behavior
Finding ways to turn large amounts of robot sensor data into useful training data
Building data collection, evaluation, replay, and training pipelines for physical AI
Taking recent research and figuring out what actually works on a robot
Designing experiments, testing them in simulation, and then getting outside and putting them on a machine
Working closely with autonomy, controls, embedded, mechanical, and product engineers
Helping define the longer-term Physical AI architecture for our robots and fleet
At Staff level, you’ll also help identify
what we should be working on next
- not just execute an existing roadmap.
What we're looking for You have deep experience in some combination of:
Machine learning / deep learning
Computer vision
Robotics and autonomous systems
C++ and Python
PyTorch or similar ML frameworks
ROS / ROS2
Real-world sensor data: cameras, LiDAR, GNSS, IMU, or similar
Training, evaluating, and deploying models on real systems
But more importantly, you know how to
make things work outside the lab .
You understand that a model running once in a notebook is very different from a model running every day on a robot.
You care about latency, compute, bad sensors, weird edge cases, changing environments, debugging, and the thousand small details between a good idea and a working machine.
You might be a great fit if
You read new robotics and AI papers and immediately want to try them.
You have side projects involving robots, cameras, drones, arms, cars, embedded systems, or strange pieces of hardware you probably didn’t need to buy.
You enjoy moving between research code and a robot with a wrench next to it.
You’re comfortable questioning the current approach and saying,
There might be a completely different way to solve this.
You don’t divide the world into AI people and robotics people.
And when something finally works on a 10,000-pound machine in the real world, that feels considerably more exciting than improving a benchmark by another 1%.
Bonus points Experience with any of the following is useful, but not required:
Vision-Language Models / Vision-Language-Action models
Imitation learning or reinforcement learning
Robot foundation models
3D perception
Neural rendering / NeRF / Gaussian Splatting
Self-supervised or unsupervised learning
Synthetic data and simulation
NVIDIA Jetson / TensorRT / edge inference
Isaac Sim or other robotics simulators
Large-scale robotics datasets
Learning from teleoperation or human demonstrations
Heavy equipment, autonomous vehicles, agricultural robots, mining, construction, or other outdoor robotics
Why Civ Robotics We have something that is still rare in Physical AI:
Real robots, doing real work, generating real data.
Our machines are deployed in environments where autonomy creates immediate economic value. That gives us the opportunity to close the loop between deployment, data, learning, and improvement.
You’ll be able to build something, put it on a robot, test it in the field, learn from it, and make the next version better.
We’re looking for someone who wants to help figure out what the next generation of real-world robots should look like and then build it.
Benefits & Perks
Comprehensive healthcare coverage (medical, dental, vision) for you and your family.
Competitive salary with growth potential.
Equity options in a fast-growing robotics company.
#J-18808-Ljbffr