Senior Infrastructure Engineer (Machine Learning) in London - AMBERES

Job Description Senior Infrastructure Engineer (Machine Learning)

Experience in HFT/ Low Latency/ Front Office or Quant Desks is ideal, but not essential

USP's:
An opportunity to be an integral member of a future AI Unicorn
Exceptional leadership team and investor backing
Future AI Unicorn with exceptional talent in the team
Working with the brightest minds in AI
Strong Equity Package
Sponsorship Available to relocate and settle in London

The business:
Amberes has partnered with one of the world's leading VC firms to help them build one of their hottest future AI Unicorn businesses building cutting-edge LLM.
The Senior Infrastructure Engineer (Machine Learning) will be influential in steering the product development, the technical success, the overall growth, and mainly the culture of a future AI Unicorn.
Must be able to work from London HQ's x4 days a week in the office

Required Credentials:
Master's degree as a minimum, ideally a PhD
Released publications in top conferences
A GitHub or other Portfolio sites
A minimum of 3+ years of being a key member of your team

Ideally have worked at a:
HFT trading experience at a Prop Trading Firm, Hedge Fund or Front Office at a Bank is ideal
Leading AI research laboratory, or a pioneering AI business

Required Expertise:

Experience in any of the below three is ideal:
1 - Taken charge of large-scale training efforts of LLMs on 500+ GPUs, significantly improving efficiency
2 - Built custom tooling for GPU farm, using 3D Parallelism, Zero Redundancy Optimizer, Mixed-Precision training
3 - Improved model training time by 100x, enabling the training of 10B+ parameter models from scratch.

Experience in creating and managing HPC clusters for ML models
Experience in efficiently serving large ML models at scale
Experience serving LLM models at scale
Able to produce and refine large-scale ML systems
Developed and orchestrated complex machine-learning pipelines

If of interest, please do apply.

Thank you,
Team Amberes