Machine Learning Engineer focusing on vulnerabilities and security of AI systems at Carnegie Mellon University. Collaborating with a team to build robust prototypes and provide solutions for government sponsors.
About the role
- Machine Learning Engineer developing advanced Deep Learning models for autonomous driving technology at Mobileye. Collaborating in a high-end algorithmic engineering team on critical computer vision challenges.
Responsibilities
- Design and implement novel Deep Learning models for object detection and scene understanding as part of a high-end algorithmic engineering team.
- Work with massive-scale real-world data and leverage breakthrough technologies to push the boundaries of perception.
- Analyze, design, and execute complex experiments to solve critical computer vision challenges in uncontrolled environments.
- Gain hands-on experience by integrating your models into production-grade autonomous vehicle stacks, seeing your code influence real-world driving.
Requirements
- Currently pursuing an M.Sc. or Ph.D. in a relevant field (Machine Learning, Computer Vision, or Computer Science) from a leading university.
- Completed B.Sc. with high achievements; solid theoretical background in Machine Learning and Deep Learning.
- Strong Python development skills and proficiency with deep learning frameworks (PyTorch is preferred/TensorFlow).
- Availability to work at least 3 days per week with at least one year remaining until graduation.
- Highly motivated, proactive, and capable of conducting independent research in a fast-paced, demanding environment.
- Advantages:
- Prior experience in a research or development role within the tech industry.
- A track record of academic publications or workshop papers in top-tier venues.
- Experience with Linux, Git, Docker, and C++.
- Hands-on experience in 2D/3D perception and familiarity with modern architectures such as Transformers, YOLO, and DeTR.
Job title
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Not specified
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Tech skills
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