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1 day ago
We are seeking an experienced systems engineer to build and manage infrastructure for data management, training, testing, deployment, telemetry, and fleet operations.
- Develop and maintain data lakes with labeling and auto-labeling pipelines, including feature store design.
- Orchestrate training workflows using Kubernetes (K8s) and Slurm; manage experiment tracking and model registries.
- Deploy models on edge devices (Jetson/Orin, TPU, x86) with support for A/B testing and staged rollouts.
The ideal candidate will have a strong background in observability tools, artifact/version control, and reproducibility practices. Experience integrating real-time operating systems (RTOS) is also desirable.
Requirements- Master's or PhD in a relevant field, 5–10+ years of experience in infrastructure engineering for robotics or ML systems.
- Proven expertise in cloud and edge CI/CD pipelines, containerization, and GPU scheduling.
- Training throughput and cost efficiency.
- Deployment latency and responsiveness.
- Maintenance and recovery speed.
Humanoids:
- Low-latency teleoperation and lab safety gate integration.
AGVs (Autonomous Ground Vehicles):
- Facility-wide OTA updates under network constraints.
Cars:
- Compliance logging and traceability for regulated environments.
Drones:
- Beyond Visual Line of Sight (BVLOS) fleet telemetry and geofence updates.
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