Senior Machine Learning Engineer
1 month ago
Who are we?
Our team is the first in the world to use autonomous vehicles on public roads using end-to-end deep learning. With our multi-national world-class technical team, we’re building things differently.
We don’t think it’s scalable to tell an algorithm how to drive through hand-coded rules and expensive HD maps. Instead, we believe that machine learning algorithms learning from experience and data will allow our driver to be more intelligent and capable of easily adapting to new environments.
Our aim is to be the future of self-driving cars: the first to deploy in 100 cities across the world bringing autonomy to everyone, everywhere.
The impact you will have:We are seeking an experienced Machine Learning Engineer to join our dynamic team. In this role, you will collaborate closely with our research team to develop, integrate, test, and scale cutting-edge algorithms, tools, and machine learning solutions for autonomous driving. Your work will directly contribute to enhancing the efficiency and speed of our model iterations, bringing innovative research ideas to life faster than ever before.
Challenges you will own:- Design and implement end-to-end neural networks for autonomous driving applications.
- Work closely with the research team to rapidly prototype and iterate on novel machine learning models.
- Optimize models for efficiency and performance, ensuring they can operate effectively in real-world autonomous driving scenarios.
- Develop and maintain a robust machine learning infrastructure that accelerates the research and development cycle.
- Continuously evaluate emerging technologies and methodologies to drive innovation within the team.
- Leverage an analytical approach that encompasses both qualitative and quantitative aspects to deliver results and insights.
- Ensure the maintenance of high-quality training data through the employment of advanced visualization and quantitative analysis techniques.
- Effectively communicating data needs within the team to optimize project success and collaboration.
- Collaborate with cross-functional teams to integrate machine learning solutions into our autonomous driving platform.
- Contribute to the creation of a collaborative and innovative engineering culture.
Must haves:
- 3+ years of postgraduate industry experience training and deploying large-scale models
- Strong foundation in machine learning and deep learning
- Advanced knowledge of model compression, quantisation, distillation, parallelism and/or pruning techniques to reduce model size and improve efficiency
- Ability to stay updated with the latest advancements in model efficiency and apply innovative solutions to enhance existing models or develop new efficient architectures
- Strong programming skills in Python, with experience in deep learning frameworks such as PyTorch, Scikit-learn, TensorRT, or similar tools for model development
- Strong teamwork and communication skills to collaborate effectively with cross-functional teams including engineers, researchers, and product managers.
Desirable:
- Understanding of hardware-specific optimizations for inference, such as optimizing models for GPUs, TPUs, or edge devices.
- PhD or MSc in Computer Science, Machine Learning, Robotics, or a related field
- A position to shape the future of autonomous driving, and thus to tackle one of the biggest challenges of our time
- Immersion in a team of world-class researchers, engineers and entrepreneurs
- Competitive compensation and stock options
- On-site chef and bar, lots of fun socials, a workplace nursery scheme and more
- Help relocating/travelling to London, with visa sponsorship
- Flexible working hours - we trust you to do your job well, at times that suit you and your team.
Wayve is built by people from all walks of life. We believe that it is our differences that make us stronger, and our unique perspectives and backgrounds that allow us to build something different. We are proud to be an equal opportunities workplace, where we don’t just embrace diversity but nurture it - so that we all thrive and grow.
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