Software Engineer – ML Infrastructure
Core
Build and maintain the software infrastructure that powers AI and machine learning workflows for robotic systems, bridging research experiments to factory floor deployment.
Role type
ML Infrastructure Software Engineer
Builds
Tooling, pipelines, and deployment systems for robot learning and AI model production
Domain
Robotics + Machine Learning Infrastructure
Deliverable
production ML models | infrastructure
Required skills
Python, PyTorch, MLOps, data pipelines, containerized workflows, GPU compute, Linux, ROS, C++
Preferred skills
Robotics software stacks, simulation environments, hardware integration
Technologies
PyTorch, ROS, Linux, Docker/Kubernetes (implied by containerized), GPU clusters
Responsibilities
Build and maintain software infrastructure for model training, experiment tracking, versioning, and deployment; Develop pipelines for collecting and processing robotic sensor and telemetry data; Support deployment of AI models onto robotic systems including simulation and runtime monitoring; Build internal tools for dataset exploration, testing, evaluation, and productionisation; Partner with AI researchers and robotics engineers to turn model requirements into scalable software systems
Seniority
Mid-level, hands-on IC