Senior ML Systems Engineer - End-to-End Robot Learning

Rhoda AI; Mountain View (CA); On-site; USD 190,000 - 270,000; Full time

Job summary

Rhoda AI in California is seeking a senior or staff-level Research Engineer or ML Systems Engineer to own the robot-learning pipeline end to end—from data collection through dataset generation, training, inference, and real-robot evaluation.

You will build validation systems, regression tests, observability, and operating practices that help researchers trust experiments and quickly identify root causes across data, software, infrastructure, hardware, or evaluation steps.

Qualifications

• Track record owning or debugging ML/robotics systems across layers.
• Proficient Python, testing, and production-grade debugging practices.
• Experience with end-to-end ML workflows from data to deployment.

Responsibilities

• Own the robot-learning pipeline end to end from data collection to real-robot evaluation.
• Define the supported golden path with code, datasets, configurations, and hardware.
• Build automated validation at every interface for timing, sensors, and schema.
• Create end-to-end regression tests including training, inference, and real-robot execution.
• Ensure training and inference consistency across data processing and model configurations.
• Make failures observable with instrumentation and debugging tools.

Skills

ML systems ownership

Robotics software

Python

CI/CD & testing

System debugging

PyTorch

Linux

Containers

Education

BS/MS in CS/Robotics or related

Tools

PyTorch

Docker/Kubernetes

Linux

Job description

Rhoda AI in California is seeking a senior or staff-level Research Engineer or ML Systems Engineer to own the robot-learning pipeline end to end—from data collection through dataset generation, training, inference, and real-robot evaluation.

You will build validation systems, regression tests, observability, and operating practices that help researchers trust experiments and quickly identify root causes across data, software, infrastructure, hardware, or evaluation steps.