Principal Machine Learning Engineer
GE HealthcareFull Time
Senior (5 to 8 years)
Key technologies and capabilities for this role
Common questions about this position
The position is remote within the United States, with occasional travel required.
This information is not specified in the job description.
Candidates need in-depth understanding of ML/DL algorithms, experience designing/training neural networks for applications like object detection, motion prediction, or multi-object tracking, fluency in Python, experience with PyTorch or similar frameworks, and advanced software engineering skills including design, testing, and code reviews.
You'll work with world-class ML engineers and research scientists on the Behaviors team, focused on perceiving dynamic scenarios and predicting agent behaviors around robo-taxis to enable self-driving vehicles.
Strong candidates have a BA, Masters, PhD or equivalent in relevant fields, proven leadership in complex technical initiatives, and bonus points for publications in top conferences, PhD in ML/CV/robotics, or AV experience; demonstrating ability to mentor, innovate, and deploy solutions is key.
Develops fully driverless robotaxis for urban transport
Motional develops fully driverless vehicles, specifically robotaxis, aimed at transforming urban transportation. Their all-electric robotaxis are designed to navigate complex city environments safely and efficiently. Motional partners with ride-hailing and delivery services, providing them with advanced autonomous vehicle technology to enhance their operations and reduce costs. A unique aspect of Motional's service is its Command Center, which allows for real-time tracking of each robotaxi, enabling human agents to monitor performance and ensure passenger safety. Unlike many competitors, Motional focuses on integrating its vehicles into existing mobility networks, making driverless technology accessible and reliable. The company's goal is to make autonomous vehicles a safe and integral part of urban transportation.