Deep Learning Researcher
TLDR
Design and train deep learning models for a custom EyeQ chip, deploying production-ready systems with software and hardware teams.
Mobileye is a pioneering force in the autonomous vehicles (AV) industry.
Join us to build the brain behind the car — a large-scale, multi-task neural network that powers the core of Mobileye’s autonomous stack.
You’ll design and train cutting-edge deep learning models tailored for our custom EyeQ chip, tackling end-to-end challenges and deploying real-world solutions.
From novel architectures and advanced training techniques to performance tuning under tight constraints, you’ll work closely with software and hardware teams to turn research into high-impact, production-ready systems.
If you’re a brilliant, hands-on researcher with a passion for shaping the future — this is your launchpad.
Our team is at the forefront of Mobileye’s most advanced AI efforts. As a central hub for deep learning innovation, we’re trusted with designing the core neural network architecture that powers the company’s flagship products. If you’re seeking a high-impact role among top-tier researchers and developers — this is the place to be.
All you need is:
Advantages:
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!
Mobileye is a technology company at the forefront of the mobility revolution, developing advanced autonomous-driving and driver-assist systems. Our cutting-edge expertise in computer vision and machine learning not only powers self-driving vehicles but also enhances mobility infrastructure through sophisticated data analysis. With innovations like REM crowdsourced mapping and Responsibility-Sensitive Safety (RSS), we are shaping the future of intelligent transport.
- Founded
- Founded 1999
- Employees
- 500+ employees
- Industry
- automotive
- Funding stage
- Public
- Stock ticker
- Publicly traded (MBLY)
- Total raised
- $3B raised