At a Glance
- Tasks: Design and optimise large-scale distributed training systems for cutting-edge AI models.
- Company: Join a leading AI research organisation at the forefront of technology.
- Benefits: Equity opportunities, competitive salary, and a chance to shape the future of AI.
- Other info: Be part of a dynamic team with excellent growth potential in a rapidly evolving field.
- Why this job: Make a real impact in AI by scaling infrastructure for frontier models.
- Qualifications: Experience with distributed training systems and strong knowledge of GPU optimisation.
The predicted salary is between 60000 - 80000 £ per year.
Paragon Alpha are working with a leading AI research organisation developing next-generation foundation models and are looking for an experienced Infrastructure Engineer to help scale the infrastructure behind frontier AI.
In this role, you'll design and optimise large-scale distributed training systems, working closely with researchers to build production-ready infrastructure capable of training models across thousands of GPUs.
You'll focus on improving performance, stability and efficiency while enabling rapid experimentation and iteration.
Stack: Kubernetes, GPUs, Megatron/Deep Speed We're looking for engineers with experience building distributed training systems for large machine learning models, strong knowledge of frameworks such as Megatron or Deep Speed , expertise in model parallelism, GPU optimisation and NCCL, and a track record of solving complex performance challenges in large-scale ML environments.
This is an opportunity to join an Open AI or Anthropic competitor at an early stage, with great opportunities for thus equity and impact on the firms growth and direction.
Contact Details:
Paragon Alpha - Hedge Fund Talent Business Recruitment Team
