Principal AI Engineer
Introduction:
Join a global, multi-disciplinary team harnessing the power of technology to shape the future of mobility. This is your opportunity to accelerate your career in the automotive sector by contributing to cutting-edge solutions that define the next generation of driving experiences.
- Design and engineer advanced audio systems and integrated tech platforms that enhance every journey
- Combine creativity, deep research, and a collaborative spirit with excellence in engineering and design
- Contribute to the evolution of in-vehicle infotainment, safety, energy efficiency, and user experience
About the Role
We are looking for a Principal AI Consultant with a solid track record in building and deploying AI-powered solutions. In this role, you’ll lead the development of machine learning systems that optimize engineering processes and boost operational effectiveness. Working within a dedicated AI team, you’ll collaborate with various departments to identify impactful challenges, craft scalable AI solutions, and embed them into enterprise platforms to achieve measurable business outcomes.
- Master’s degree in Computer Science or a related technical discipline
- 7+ years of experience designing, developing, and deploying AI/ML solutions in production environments, including full system integration
- Proven success in delivering scalable Generative AI solutions, from prototyping to deployment and performance evaluation
- Expertise in Large Language Models (LLMs), including prompting techniques and optimizing inference processes
- 4+ years of hands-on experience with AI/ML workloads on public cloud platforms such as AWS or Azure, with strong understanding of key services for compute, orchestration, and deployment
- Advanced Python programming skills, including OOP, TDD, and clean coding principles
- Strong foundation in ML system architecture, covering areas such as data pipelines, lifecycle management, monitoring, and MLOps best practices
- Ability to engage across disciplines and lead technical discussions with data scientists, engineers, product owners, and operational teams