Machine Learning Engineer (optimization) – Startup LLM – up to £200k +equity – London

Do you have experience with optimization and quantization for ML models on HPC clusters?

Are you passionate about building groundbreaking technology and shaping the future of AI?

Are you excited by the thought of starting a company from the ground up? If so, we have the perfect opportunity for you.

The challenge

We’re a young start up, putting together our founding team to join us in building an application to train and evaluate LLM applications, in order to be most efficient in compute usage, protect from vulnerabilities, reduce model failure and be aligned with human intent.

There are 7 of us so far, with an aim to get to 15 by the end of the year. We’ve secured $5m in seed funding to kick us off and aim to go for Series A in early 2025!

We’re looking for an experienced Machine Learning Engineer that has implemented SOTA Research and quantization techniques to optimize ML pipelines to enable people to ship their models faster and more efficiently.

About you

You’ll have experience applying quantization techniques, pruning, distributed training and optimizing ML pipelines for training and deploying on GPU, managed HPC clusters, implemented inference servers.

You’ll be able to define memory footprint, reduce memory consumption and improve data loading for ML Pipelines.

Here are some of things we’d expect you to have:

Experience in ML quantization, PEFT, DeepSpeed, ONNX, TensorRT etc Experience in Deep Learning using PyTorch Library Experience with Kubernetes Familiar with inference servers such as multi-LoRa, LoRA Exchange, TitanML etc Experience creating/managing multi node HPC clusters Experience with Workload Managers like SLURM, Kepler, Moab etc Experience working with some of the more recent LLMs (OpenAI, Mistral, Claude, LLaMA etc)

Whats in it for me?

As a start-up, the fancier perks are in the pipeline but being a founding member you’ll receive substantial equity alongside a generous base salary of £125-£200k, 4% employer contribution towards pension and 25 days holiday.

Interested?

If you think you fit the bill, get in touch by clicking the ‘apply now’ button or get in touch with me by the following:

Email me at Call me on