Experienced Deep Learning Algorithm Developer – Object Perception Group
Overview
- Added in 30 days
- 68
- At this company, still open
Skills named in this posting
- Python
- PyTorch / TensorFlow
We are looking for an experienced Deep Learning Algorithm Developer to join one of our teams developing perception technologies for autonomous driving.
Our group tackles diverse challenges — from object detection and scene understanding to 3D perception — using large-scale, real-world in-house datasets and state-of-the-art deep learning models.
What will your job look like:
• Develop and train neural networks for complex perception tasks in real-world driving environments.
• Design and analyze deep learning pipelines, from data to deployment.
• Collaborate with algorithm, software, and data experts to deliver production-ready models.
• Research and apply new methods in computer vision, 3D perception, and multi-task learning to improve performance and efficiency.
All you need is:
• M.Sc. in Computer Science, Electrical Engineering, or a related field.
• At least 2 years of industry experience developing deep learning–based computer vision algorithms.
• Strong Python programming skills and hands-on experience with PyTorch.
• Solid understanding of deep learning and computer vision.
Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!
Apply on the employer's site
Original posting: jobs.eu.lever.co
RISC-V ecosystem
Mobileye Vision Technologies Ltd. in the RISC-V ecosystem
RISC-V International: Strategic
Mobileye is an Israeli subsidiary of Intel corporation that develops vision-based self-driving car and advanced driver-assistance systems providing warnings for collision prevention and mitigation.
- Uses RISC-V in automotive silicon: EyeQ Ultra is described as a RISC-V processor targeting Level-4 autonomous driving
- Exhibited in the RISC-V booth at Embedded World 2023
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