Senior Deep Learning Researcher
Posted 19 days ago · 56 applicants
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The role in plain words
This role involves designing and training large-scale, multi-task deep learning models for Mobileye's autonomous vehicle stack. You will build end-to-end pipelines from data preparation to deployment, optimizing models to run under tight constraints on custom EyeQ hardware. The work requires collaborating with software and hardware teams to turn research into production-ready systems.
- PhD in Computer Science or a related discipline (exceptional MSc candidates will be considered)
- 4+ years of hands-on experience developing deep learning algorithms in Python
- Experience building end-to-end DL pipelines: data preparation, training, evaluation, and deployment
- Proficiency in at least one deep learning framework (e.g., TensorFlow, PyTorch)
- Excellent problem-solving skills and a research-oriented mindset
- Industry experience in DL or software development
- Familiarity with hardware-aware model optimization
- Experience with cloud platforms (e.g., AWS), Docker, and Linux environments
- Publications or contributions in the fields of deep learning, neural architecture search, knowledge distillation or multi-task learning
Extracted from the job description · kept up to date automatically
Who this suits
This role suits hands-on researchers with a PhD or an exceptional MSc in Computer Science, along with at least four years of experience developing deep learning algorithms in Python. It is less ideal for those without strong experience in building end-to-end deep learning pipelines or those looking for a purely theoretical research role without deployment responsibilities.
Full job description
Original listing · kept for referenceMobileye 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:
• PhD in Computer Science or a related discipline (exceptional MSc candidates will be considered).
• 4+ years of hands-on experience developing deep learning algorithms in Python.
• Experience building end-to-end DL pipelines: data preparation, training, evaluation, and deployment.
• Proficiency in at least one deep learning framework (e.g., TensorFlow, PyTorch).
• Excellent problem-solving skills and a research-oriented mindset.
Advantages:
• Industry experience in DL or software development.
• Familiarity with hardware-aware model optimization.
• Experience with cloud platforms (e.g., AWS), Docker, and Linux environments.
• Publications or contributions in the fields of deep learning, neural architecture search, knowledge distillation or multi-task learning.
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!
Questions about this role
- This listing did not state a salary. We only show pay when the employer publishes it.
- PhD in Computer Science or a related discipline (exceptional MSc candidates will be considered), 4+ years of hands-on experience developing deep learning algorithms in Python, Experience building end-to-end DL pipelines: data preparation, training, evaluation, and deployment, Proficiency in at least one deep learning framework (e.g., TensorFlow, PyTorch), Excellent problem-solving skills and a research-oriented mindset