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The Perception team is looking for a machine learning engineer to develop cutting-edge Computer Vision modules to enhance the on-board perception of our robotic fleet, directly impacting safety and fleet efficiency. In this role, the ideal candidate will work on the full design and development cycle, including data collection, data set creation, machine learning models design and implementation.
Job Responsibility:
Design and develop in-cabin Computer Vision ML modules for safety critical perception and monitoring applications
Implement Perception model architectures and sophisticated training techniques
Build high quality datasets leveraging all the inputs from our sensor stack and the overall large scale data we have collected
Validate and optimize your solutions using real-world driving scenarios, directly contributing to the safety and reliability of our autonomous system
Requirements:
Bachelor's Degree in Computer Science and/or Computer Engineering
3+ years with a Modern Computer Vision and Machine Learning background, specifically on 3D reconstruction, detection, classification, semantic segmentation
Experience with training and deploying Deep Learning models
Background in C++ and/or python
Excellent communication skills
Creative mindset willing to challenge the norms
Nice to have:
Self-driving industry experience
Experience delivering ML model integration in latency-sensitive systems