Machine Learning Engineer

Overview

Location: Remote or Hybrid (London) - preference based

About

CATCHES are backed by some of the most influential names in luxury fashion globally. We blend advanced 3D rendering, AI and VFX techniques to deliver unparalleled shopping experiences for luxury fashion.

Role

A senior engineering role writing production-grade code and personally implementing the architectures you design for scale.

Primary Focus: Model Selection, Custom VLM/LLM Development, ML System Integration.

• Custom VLM: Develop and own VLMs for high-fidelity image and video generation tasks. Owning model correctness, training strategy, and system architecture with support from inference engineering experts.
• LLM Implementation: Implement and optimise LLMs for diverse use cases, ranging from user-facing conversational agents (chat) to miscellaneous backend utility tasks e.g. parsing, categorisation.
• Model Scouting: Continuously benchmark state-of-the-art open-source models e.g. Qwen, Llama, Flux, SDXL or similar to ensure we are always utilising the best tools available.
• Architecture & Integration: Design and code the high-level architecture, bridging Python-based AI microservices with the core platform (C#).

• Languages
  :
  Python (deep expertise), C# (familiarity / willingness to integrate).
• Frameworks: PyTorch (deep expertise), Hugging Face ecosystem or similar.
• Model
  
  Experience:
  
  Deep hands-on experience with VLMs (for video/image), LLMs
• (Qwen, Llama or similar), and Generative Models (Flux, Stable Diffusion or similar).
• 3D (nice to have): Exposure to or interest in 3D generation pipelines.

• Remote with optional co-working access.
• Be part of an experienced team that values shipping, experimentation and autonomy.
• Contribute to product and architecture decisions.
• Use cutting edge tech to deliver once in a generation consumer facing technology at scale.