Path Robotics designs robotic welding systems that incorporate AI and machine learning for enhanced precision and adaptability. These systems automate repetitive tasks, enabling manufacturers to increase productivity while minimizing upfront costs. Backed by Drive Capital.
About the role
We're looking for a Software Engineer to build and maintain the infrastructure that powers our AI and machine learning workflows. You'll be the bridge between our AI research team and production — building the tooling, pipelines, and deployment systems that let models go from experiment to factory floor. This is a role for someone who thinks in systems but speaks ML: you understand what researchers need, and you know how to build reliable software around it.
What they're looking for
- You have 3–6 years of software engineering experience, with solid exposure to ML infrastructure, MLOps, or AI-enabled systems
- You write strong production software in Python, and ideally also have experience with C++, ROS, or robotics software stacks
- You have experience with PyTorch and a practical understanding of the software systems needed to support AI model development
- You are comfortable with data pipelines, simulation environments, containerised workflows, and GPU compute in Linux environments
- You enjoy working across AI and robotics, and can support the full path from data collection and testing through to deployment on real systems
More about this role
At Path Robotics, we’re attacking a trillion dollar opportunity - doing things that have never been done before to support an industry hurting from a lack of skilled labor. Big, hard problems are what Path tackles every day, and our people are our greatest asset to get that job done. Our intelligent, hardworking team of people do the impossible every single day, yet remain incredibly kind, humble, and always ready to support one another.
We're looking for a Software Engineer to build and maintain the infrastructure that powers our AI and machine learning workflows. You'll be the bridge between our AI research team and production — building the tooling, pipelines, and deployment systems that let models go from experiment to factory floor. This is a role for someone who thinks in systems but speaks ML: you understand what researchers need, and you know how to build reliable software around it.
- Build and maintain the software infrastructure that supports robot learning, including model training, experiment tracking, versioning, and deployment.
- Develop pipelines and tools for collecting, processing, and curating large-scale robotic sensor and telemetry data.
- Support deployment...
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