AR
$197,000 – $307,000
Listed on Agility Robotics’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
Build the ML infrastructure and platform layer that powers Agility's fleet of humanoid robots, architecting systems for data collection, model training, evaluation, and deployment at scale. This role suits senior engineers with hands-on MLOps and cloud platform experience who want to directly enable production AI systems in robotics.
Our summary, not Agility Robotics’s wording. The full posting is on their site.
Skills this role names
- Amazon Web Services (AWS)
- Apache Airflow
- AWS Cloud Development Kit (CDK)
- Kubeflow
- Kubernetes
- Microsoft Azure
- MLflow
- Python
- Terraform
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What they ask for
Required
- 5+ years of software engineering experience
- 2+ years working on ML infrastructure, data platforms or MLOps systems in production
- Experience building experiment tracking, model registries, training pipelines or deployment systems
- Knowledge of orchestration and tracking tools like MLflow, WandB, Airflow or Kubeflow
- Cloud platform proficiency (AWS, GCP or Azure)
- Container and Infrastructure-as-Code experience
- Hands-on experience with multimodal data (sensor logs, camera streams, behavior traces)
- Cross-functional collaboration with research scientists and data engineers
Nice to have
- Robotics, autonomous vehicles, drones or embedded ML experience
- Open-source ML infrastructure or MLOps tooling contributions