Join us in building the brain behind the car - a large-scale, multi-task neural network that powers the core of autonomous driving stack.
In this role, youll design, train and evaluate cutting-edge deep learning models optimized 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 compute constraints, youll work closely with software and hardware teams to turn research into high-impact, production-ready systems.
If youre an outstanding student with a passion for shaping the future of AI and autonomous driving - this is your launchpad.
What will your job look like:
Design, implement and train deep learning algorithms to solve complex real-world problems
Collaborate with cross-functional teams to understand requirements and deliver robust solutions
Conduct research, evaluate existing models and techniques, and propose innovative approaches to improve performance and accuracy
Optimize deep learning algorithms and DNN architectures for performance, efficiency, and scalability
Stay up to date with the latest advances in deep learning, AI architectures, and multi-task learning, and apply them in production settings