Lead Applied Scientist, TinyML London

Wayve Technologies Ltd.; London; On-site; GBP 125,000 - 150,000; Full time

Job summary

An innovative firm is seeking a Lead Applied Scientist to join their dynamic London team, focusing on TinyML and autonomous systems. In this pivotal role, you will design and optimize ultra-efficient foundation models that enhance the adaptability and efficiency of autonomous vehicles. Your work will directly influence the future of transportation, collaborating with top-tier researchers to push the boundaries of AI. This role offers a unique opportunity to make a tangible impact in a field that is rapidly evolving, all while enjoying a hybrid working environment that promotes innovation and collaboration. If you're passionate about AI and want to shape the future of autonomous technologies, this is the perfect opportunity for you.

Qualifications

• 7+ years of ML engineering experience in an industrial research environment.
• Strong programming skills in Python and deep learning frameworks.

Responsibilities

• Design and optimize ultra-efficient foundation models for autonomous systems.
• Collaborate with researchers to advance autonomous driving technology.

Skills

Machine Learning Engineering

Applied Science

TinyML

Reinforcement Learning

Python Programming

Deep Learning Frameworks

Data Handling

Education

MS in Machine Learning

PhD in Computer Science

Tools

PyTorch

NumPy

Pandas

C++

CUDA

Job description

The role

We are seeking a Lead 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. Your work will involve but not limited to:

• 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.

About you

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.

Essential

• 7+ 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

• Track record of publications at top-tier conferences like NeurIPS, CVPR, ICRA, ICLR, CoRL etc.
• Strong software engineering experience in Python and other relevant languages (e.g., C++ and CUDA)
• Experience bringing an ML research concept through to production and at scale

This is a full-time role based in our office in London. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. We operate core working hours so you can determine the schedule that works best for you and your team.

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