Agility Robotics is looking to develop and improve the AI infrastructure and models that enable their robot, Digit, to operate autonomously, efficiently, and safely in workplaces across the globe.
Requirements
- 8+ years of professional experience in AI infrastructure, ML engineering, or MLOps roles.
- Strong software engineering skills, particularly in Python; proficiency in developing scalable, maintainable libraries and tools.
- Experience building and maintaining ML pipelines, from dataset curation to training, evaluation, and deployment.
- Familiarity with training frameworks such as PyTorch or TensorFlow.
- Practical understanding of data-driven model development, including dataset management, reproducibility, and performance monitoring.
- Experience deploying machine learning models into real-time or embedded systems.
- Familiarity with experiment tracking tools (e.g. MLflow, Weights & Biases) and orchestration systems (e.g.Kubernetes)
Responsibilities
- Develop data pipelines and curation workflows to maintain high-quality datasets for perception, locomotion, and manipulation tasks.
- Design, build, and maintain scalable AI infrastructure, including shared libraries, model training pipelines, and evaluation frameworks.
- Build dashboards, visualization tools, and reusable metrics to monitor and improve model performance and operational readiness.
- Define and implement testing, validation, and reproducibility tools to ensure reliable deployment of models on Digit.
- Collaborate with skills and control teams to integrate models efficiently into production systems, including real-time execution environments.
- Promote best practices for data management, experiment tracking, and ML operations across the AI Engineering organization.
Other
- Excellent communication skills and a collaborative mindset for working across AI, controls, and robotics software teams.
- Current authorization to work in the United States.
- Applicants must have a degree (not specified which type) and relevant experience.
- Must be willing to work in a U.S.-based role.
- Must be willing to relocate (relocation assistance provided for eligible roles)
