Applied AI Scientist (Ph.D) – On‑Site

About the role

We are looking for a hands‑on Applied AI Scientist to join our core R&D team and drive the creation of next‑generation AI systems for autonomous driving. The position bridges applied research and production, allowing you to move from reading papers to shipping real‑time predictive models that run on embedded automotive platforms.

Key responsibilities

• Own the end‑to‑end research‑to‑deployment cycle for predictive driving models, from literature review and prototyping to production integration.
• Design, implement and iterate on real‑time predictive models, including vision‑language, motion‑prediction and inverse‑reinforcement‑learning approaches.
• Bridge cloud‑scale training with edge deployment by applying model compression, quantization, speculative decoding and other efficient‑inference techniques.
• Evaluate and integrate state‑of‑the‑art AI methods into the autonomy stack and collaborate closely with internal R&D teams to unblock technical challenges.

Required profile

• Ph.D. in Computer Science, Electrical Engineering, Machine Learning, Robotics or a related field.
• Strong publication or deployment track record in deep learning, computer vision, reinforcement learning, imitation learning, vision‑language models or motion prediction.
• Demonstrated ability to turn research papers into shipped systems.
• Solid mathematical foundations in probability, optimization and statistics.

Required skills

• Proficient programming in Python; experience with C++ is a plus.
• Hands‑on experience with PyTorch, distributed training and model‑optimization pipelines.
• Familiarity with CUDA, GPU optimization, model quantization, distillation and efficient inference on edge devices.