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- Tasks: Develop and optimise machine learning models for high-fidelity image and video generation.
- Company: Join CATCHES, a leader in luxury fashion tech with a creative culture.
- Benefits: Remote work options, collaborative team, and opportunities for innovation.
- Why this job: Work with cutting-edge AI tech to revolutionise luxury shopping experiences.
- Qualifications: Expertise in Python and PyTorch, with experience in VLMs and LLMs.
- Other info: Dynamic environment that encourages experimentation and career growth.
The predicted salary is between 36000 - 60000 £ per year.
Location: Remote or Hybrid (London) - preference based
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.
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.
Responsibilities
- 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#).
Qualifications
- Languages: Python (deep expertise), C# (familiarity / willingness to integrate).
- Frameworks: PyTorch (deep expertise), HuggingFace 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.
Working at CATCHES 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.
Machine Learning Engineer in London employer: CATCHES
Contact Detail:
CATCHES Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups or webinars, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving VLMs and LLMs. Share your work on GitHub or personal websites to give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail, especially how you tackled model selection and system integration.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight your experience with Python, PyTorch, and any relevant models you've worked with.
We think you need these skills to ace Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with Python, PyTorch, and any relevant VLM/LLM projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for AI and luxury fashion, and explain why you’re excited about the opportunity at CATCHES. Let us know how your background makes you a perfect fit for our team.
Showcase Your Projects: If you've got any personal or professional projects related to machine learning, make sure to include them. We love seeing real-world applications of your skills, especially in VLMs and LLMs. It gives us a better idea of what you can bring to the table!
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts and you’ll be all set!
How to prepare for a job interview at CATCHES
✨Know Your Models Inside Out
Make sure you’re well-versed in the latest VLMs and LLMs mentioned in the job description. Be prepared to discuss your hands-on experience with models like Qwen, Llama, and Flux. This shows you’re not just familiar with the theory but have practical knowledge that can be applied.
✨Showcase Your Coding Skills
Since this role involves writing production-grade code, brush up on your Python and C#. Be ready to demonstrate your coding abilities, perhaps through a live coding exercise or by discussing past projects where you implemented complex architectures.
✨Understand the Architecture
Familiarise yourself with how Python-based AI microservices integrate with other platforms, especially C#. Being able to articulate your understanding of system architecture will impress the interviewers and show that you can contribute to their tech stack effectively.
✨Stay Updated on Industry Trends
CATCHES values innovation, so keep an eye on the latest advancements in AI and 3D rendering. Bring examples of recent developments or tools you’ve benchmarked, and be ready to discuss how they could benefit the company’s projects.
