Machine Learning Engineer at Watney Robotics Inc in San Francisco

Job description

• Application
• Our Mission
• Expand human ambition in the physical world.
• Critical infrastructure is constrained by labor shortages, hazardous working conditions, and operational complexity. Watney builds and deploys autonomous robotic systems that increase the speed and capacity of buildout, starting with data centers.
• At Watney, ML engineers turn a live fleet of robots into better models. The fleet produces large volumes of video from real work in the field, and turning that data into a model that performs better on the next deployment is one of the hardest problems at the company. The model work spans multiple kinds of tasks: what the robot sees, decides, and acts on.
• You will help decide the path forward, staged from imitation learning toward broader generalization: run training experiments, help curate and label the data behind them, and help evaluate what works on a real fleet.

Responsibilities

• Run and evaluate training experiments as we scale our models.
• Curate and clean the data those experiments train on.
• Help evolve how we label and structure new data.
• Track the metrics that separate a model that helps from one that doesn't.
• Work with Teleoperations to understand and improve the data at its source.

Requirements

• Have trained models on real-world data pulled from actual operation.
• Have worked with imitation learning, reinforcement learning, or a similar method for control.
• Write production ML code (Python, PyTorch, etc).
• Are comfortable cleaning and curating messy, real-world data.

Skills

Required

• Training models on real-world data
• Imitation learning
• Reinforcement learning
• Production ML code (Python, PyTorch)
• Data cleaning and curation