【Redacted】MLOps / Machine Learning Platform Engineer (Autonomous Driving)
This role focuses on building and operating the machine learning platform that supports autonomous driving R&D. You will work across the full ML workflow—from data processing and model training to deployment—enabling continuous model improvement using large-scale driving data.
Role Overview
Develop and operate training pipelines for tasks such as object detection
Build infrastructure for model monitoring, evaluation, and deployment to vehicles
Develop pipelines for visualizing and analyzing large-scale unstructured sensor data
Build and maintain annotation systems and sensor-data transformation pipelines
Drive improvements and automation within the ML platform
What Makes This Role Interesting
Work with diverse data types including camera and point cloud inputs
Build safe and scalable evaluation workflows integrated with simulation systems
Design platforms that enable continuous model improvement using real-world driving data
Contribute to the backbone infrastructure that supports autonomous driving development
Collaborate closely with engineers across ML, perception, data, and cloud domains
Required Skills
3+ years of web application development and operations
Hands-on development experience with Python or Go
Experience building and operating on cloud platforms (e.g., AWS, GCP, Azure)
System architecture and API design experience
Experience building and maintaining CI/CD pipelines
Foundational understanding of machine learning concepts
Preferred Skills
Experience building or operating ML platforms / MLOps systems
Experience developing systems using large-scale models such as LLMs
Technical leadership or team lead experience
Experience with large-scale data processing or data platform development
Ideal Candidate
Comfortable driving work forward amid ambiguity
Motivated to contribute to the ML infrastructure supporting autonomous driving
Curious, fast-learning, and proactive in adopting new technologies
Able to collaborate across diverse teams and backgrounds
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