- 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.
What you will bring
Must haves: - 3+ years of postgraduate industry experience training and deploying large-scale models
- Strong foundation in machine learning and deep learning
- Experience bringing research concepts through the full ML development cycle and into production
- 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.
Bonus: - Advanced knowledge of model compression, quantisation, distillation, parallelism and/or pruning techniques to reduce model size and improve efficiency
- 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
What we offer you
- A position to shape the future of autonomous driving and embodied AI, 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 share options
- Daily lunches, team socials, funded club/society activities and company-wide learning and development
- Help relocating to Vancouver, with potential for visa sponsorship
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.Wayve focuses on Machine Learning, Artificial Intelligence, Services, Electric Vehicles, and Software. Their company has offices in Cambridge and Cambridge. They have a small team that's between 11-50 employees. To date, Wayve has raised $20M of funding; their latest round was closed on November 2019.
You can view their website at or find them on Twitter and LinkedIn.
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Senior Machine Learning Engineer - Vancouver, Canada - Wayve
Description
Who are we?
Our team is the first in the world to use autonomous vehicles on public roads using end-to-end deep learning, computer vision and reinforcement learning. Leveraging our multi-national world-class team of researchers and engineers, we're using data to learn more intelligent algorithms to bring autonomy for everyone, everywhere. We aim to be the future of self-driving cars, learning from experience and data.
Impact expected
We are seeking an experienced Machine Learning Engineer to join our foundational Vancouver office. In this role, you will collaborate closely in 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 efficacy and efficiency of our models, and our iteration speed, bringing innovative research ideas to life faster than ever before.
Challenges you will own
You'll be working on some of the world's hardest problems, and able to attack them in new ways. You'll be a key technical contributor within our diverse, cross-disciplinary team, helping teach our robots how to drive safely and comfortably in complex real-world environments. This encompasses many aspects of engineering and optimization across perception, prediction, planning, and control, including: