Description

You will define and drive the technical roadmap and strategy for end-to-end AI machinery.

Responsibilities

• Oversee the design, development, and testing of the E2E AI machinery, including its interaction with data sources and model repositories.
• Collaborate with data engineering and infrastructure leads to define the overall architecture of the AI machinery ecosystem.
• Guide the setup of a development framework that enables fast evaluation and integration of emerging E2E AI solutions.
• Guide the transition of research prototypes to production-ready solutions, ensuring performance on automotive-grade hardware.
• Mentor and lead a team of AI scientists and engineers.

Required Skills

• 10+ years of experience in software development and system engineering for autonomous driving or ADAS applications.
• Proven industry experience releasing AI-based L2+ systems with successful product deployments.
• Deep knowledge of E2E AI stack solutions and training algorithms, including reinforcement learning and imitation learning.
• Deep knowledge of AI frameworks such as TensorFlow and PyTorch.
• Deep knowledge in model optimization and embedded deployment of E2E AI stacks to automotive hardware.
• Deep knowledge of cloud-based scalable training pipelines, MLOps, and CICD for training AI models.
• Proficiency in C++ and Python.
• Experience with system validation and testing (SIL/HIL).

Key Skills

Education

Any Graduate