Staff Machine Learning Engineer, Wayve

• 5+ years of postgraduate industry experience training and deploying large-scale models on distributed systems
• Strong foundation in machine learning and deep learning
• Experience leading a technical/research agenda aligned with larger organisation or company goals
• Experience bringing research concepts through the full ML development cycle and into production
• Experience working in a metrics and data driven environment
• 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

• 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
• You'll be working on some of the world's hardest problems, and able to attack them in new ways
• You'll be a technical leader 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
• Design and implement end-to-end neural networks and related technologies for autonomous driving applications
• Work closely in our 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 tools and infrastructure that accelerates the research and development cycle
• Build metrics and dashboards that give us insight into progress and focus us on solving the right problems
• 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 communicate 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