Research Engineer
We’re partnering with an early-stage AI startup building next-generation foundation models that significantly improve the performance of LLMs when working with structured data.
The company is doubling in size this year, with ambitious research goals and exciting growth opportunities. This is a high-ownership, high-impact role where you will help shape the research direction from day one.
As a Research Engineer, you will work closely with researchers to develop state-of-the-art models and bring them into production.
The Role
- Own the model pre-training stack and optimise training infrastructure
- Design and implement optimisations to reduce latency and improve scalability
- Write low-level GPU kernels to address performance bottlenecks
- Develop internal tooling to enable rapid experimentation and iteration
- Contribute to publications at leading international AI conferences
Your Background
- PhD or Master’s degree in Machine Learning, Computer Science, or a related field
- Proven experience in ML systems, with a focus on training and inference optimisation
- Experience writing CUDA kernels
- Exceptional proficiency in Python and PyTorch
- Experience with distributed training frameworks (e.g. Triton) and cluster environments (e.g. SLURM)
- Research publications at conferences such as NeurIPS, ICML, ICLR, or JMLR would be beneficial, but are not essential
- Experience working with structured data (tabular/time-series) is a plus
If this sounds like the perfect match, please apply with your most recent CV, and someone from the team will be in touch to discuss in detail.