Software Engineer, Machine Learning Platform

The role 

We are looking for a Software Engineer to help build the Wayve Machine Learning platform. The ML Platform team owns the machine learning training infrastructure and works with users to ensure that this infrastructure is reliable and efficiently utilised.

Key responsibilities:

• You will be part of a growing group focussed on making training infrastructure available to users, for distributed training of large models.
• You will be working across functions with machine learning research engineers to optimise models so that they can be trained efficiently, saving both money and researcher time.
• You will have opportunities to develop new skills, especially in model optimisation.

Examples Projects:

• Working with machine learning researchers to optimise ML models, using the latest tooling like NVIDIA NSight.
• Training job scheduling and orchestration e.g. tooling to schedule long running jobs at off-peak times.
• Tooling which provides thousands of GPUs simultaneously to our driving simulator, which we use to test the driving performance of our models off road.

About you  

In order to set you up for success in this role at Wayve, we’re looking for the following skills and experience.  

Essential

• Minimum of 5 years experience within Software Engineering, ideally ML Infrastructure / Platform Engineering
• Proficiency in Python
• Knowledge of software engineering practices - what makes code reusable and extensible.
• Experience  working with concurrent, parallel and distributed computing.
• Passion for infrastructure: building internal tooling and frameworks.
• Experience with cloud infrastructure, preferably Azure
• Experience with Docker, Kubernetes and Terraform 

Desirable

• Experience profiling and optimising ML models e.g. with NVIDIA NSight.
• Experience working with at least one ML framework e.g. Pytorch, Tensorflow, ONNX and TensorRT

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