Senior Applied Scientist, Wayve

• You are an applied scientist with a deep understanding of AI/ML and a specific focus on TinyML
• You thrive in environments where innovation meets real-world application, and you are driven by the desire to see your research make a tangible impact on autonomous technologies
• 5+ years of ML engineering / applied science experience in an industrial research environment
• Experience in GenAI, EfficientAI, LLMs, World Models, Reinforcement Learning, or Autonomous Driving
• Passion for working in a team on research ideas that have real-world impact
• Strong programming skills in Python, with experience in deep learning frameworks such as PyTorch, numpy, pandas, etc
• Several years of experience working on machine learning algorithms and systems
• A good grasp of machine learning literature
• Comfortable working with large quantities of image and video data
• Good insight into the practical aspects of training, validation, testing, and metrics for deep learning features/models
• MS or PhD Machine Learning, Computer Science, Engineering, or a related technical discipline, or equivalent experience

Desirable

• We are seeking a senior applied scientist to join our London team where we have been building foundation models for embodied intelligence including LINGO and GAIA!
• We are prioritising someone with a passion for TinyML to join our dynamic London team
• In this role, you will be instrumental in designing and optimizing ultra-efficient foundation models tailored for autonomous systems and embodied AI
• You will work on the cutting edge of AI/ML, contributing to models that are both powerful and resource-efficient, enabling seamless integration into real-world autonomous environments
• Your efforts will directly impact the future of autonomous vehicles, enhancing their adaptability, reliability, and efficiency through innovative approaches such as model-free and model-based reinforcement learning, efficient vision-language models, and more
• In this role, you will be at the forefront of designing and optimizing foundation models that are both powerful and resource-efficient, tailored for the unique demands of embodied AI and autonomous systems
• Design and optimize ultra-efficient foundation models specifically tailored for autonomous systems and embodied AI
• Develop and refine techniques such as model-free and model-based reinforcement learning, and efficient vision-language models to improve the adaptability, reliability, and efficiency of autonomous systems
• Collaborate with world-class researchers and engineers to push the boundaries of AI, contributing significantly to the evolution of autonomous driving technology
• Influence the future of autonomous vehicles, helping to shape a smarter, safer, and more efficient transportation ecosystem