AI Research Engineer - AI Safety Platform

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

Job summary

A Europe-based deep learning company is seeking an AI Engineer to develop and scale LLMs and VLMs from scratch. This hands-on role will focus on optimising distributed GPU systems and building advanced architectures while working remotely. The ideal candidate should have experience with large-scale GPU training and frameworks including PyTorch and Triton, and will engage in innovative projects aimed at enhancing the efficiency and capabilities of AI models. Competitive salary up to £200k with equity offered.

Qualifications

• Experience with LLMs and VLMs training from scratch.
• Familiarity with distributed GPU systems.
• Proficient in building and optimising training pipelines.

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.

Skills

Large-scale GPU training

Triton

CUDA

ML experimentation

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.