Senior Machine Learning Engineer

Key Skills

Algorithms, Deep Learning, Effective communication skills, GPUs, Machine learning techniques, Optimization, Python Programming, PyTorch, Scikit-learn, TensorRT

Job Description

Where you will have an impact

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:

• Designing and implementing end-to-end neural networks for autonomous driving applications
• Working closely with the research team to rapidly prototype and iterate on novel machine learning models
• Optimizing models for efficiency and performance, ensuring they can operate effectively in real-world autonomous driving scenarios
• Developing and maintaining a robust machine learning infrastructure that accelerates the research and development cycle
• Continuously evaluating emerging technologies and methodologies to drive innovation within the team
• Leveraging an analytical approach that encompasses both qualitative and quantitative aspects to deliver results and insights
• Ensuring 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
• Collaborating with cross-functional teams to integrate machine learning solutions into our autonomous driving platform
• Contributing to the creation of a collaborative and innovative engineering culture

What you will bring to Wayve

Essential

• 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

What we offer you

• The chance to be part of a truly mission driven organisation and an opportunity to shape the future of autonomous driving. Unlike our competitors, Wayve is still relatively small and nimble, giving you the chance to make a huge impact
• Competitive compensation and benefits
• A dynamic and fast-paced work environment in which you will grow every day - learning on the job, from the brightest minds in our space, and with support for more formal learning opportunities too
• A culture that is ego-free, respectful and welcoming (of you and your dog) - we even eat lunch together every day
• Benefits such as an onsite chef, workplace nursery scheme, private health insurance, cycle scheme, therapy, yoga, two onsite bars, large social budgets
• 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 also operate core working hours so you can be where you need to be for family and loved ones too. Teams determine the routines that work best for them.