AI Research Engineer - AI Safety Platform

Harnham; Remote; GBP 170,000 - 200,000; Full time

Job summary

A leading deep learning company based in Europe is seeking an AI Engineer to develop and train frontier-level LLM models from scratch. This hands-on, research-driven role involves optimizing large-scale GPU systems and contributing to advanced architectures like Mixture-of-Experts. The ideal candidate will collaborate closely with elite engineers on innovative AI projects. The position offers a competitive salary up to £200k and equity, with a fully remote working model.

Qualifications

• Hands-on experience with training LLMs and VLMs.
• Proficiency in writing and optimizing CUDA / Triton kernels.
• Ability to work within distributed systems.

Responsibilities

• Train LLMs / VLMs from scratch using distributed frameworks.
• Build and optimise multimodal training pipelines.
• Develop and refine Mixture-of-Experts architectures.
• Write and optimise CUDA / Triton kernels.
• Improve training stability, speed, and memory efficiency.

Skills

Large-scale GPU training

Triton / CUDA

Mixture-of-Experts architecture

Multimodal training pipelines

AI model optimization

Tools

PyTorch

Megatron

DeepSpeed

Job description

Do you want to build frontier-level LLM models from scratch?

Have you worked on large-scale GPU training, Triton / CUDA, or MoE systems?

Are you ready to join one of Europe’s most technical deep-learning teams?

A Europe-based deep learning company is building the next generation of foundation models. Think of a smaller, faster, highly technical version of the major frontier labs – focused on LLM / VLM training, GPU efficiency, safety layers, and advanced architectures. They are preparing for their next funding milestone and operate with an extremely high technical bar.

They are hiring an AI Engineer to focus on training, scaling, and optimising large models. This role is hands‑on, research‑driven, and sits at the core of model creation. The AI Engineer will train LLMs and VLMs from scratch, optimise distributed GPU systems, and contribute to new architectures including Mixture‑of‑Experts and multimodal pipelines. You’ll work closely with a small team of world‑class engineers on one of the most technical problems in AI.

Key responsibilities

• Train LLMs / VLMs from scratch using distributed frameworks
• Build and optimise multimodal training pipelines (text, image, audio)
• Develop and refine Mixture‑of‑Experts architectures
• Write and optimise CUDA / Triton kernels
• Improve training stability, speed, and memory efficiency
• Experiment with new architectures, scaling laws, and data mixtures

Key details

• Salary : Up to £200k + equity (0.1–0.3%)
• Working model : UK, 100% remote
• Stack : PyTorch, Megatron, DeepSpeed, Triton / CUDA, multimodal architectures

Interested? Please apply below.