Asks for

The ad says“Familiar with software development practices including version control, CI/CD, containerization, and monitoring for MLOps”
The ad says“Hands-on professional experience in fine-tuning and deploying machine learning solutions end-to-end, with a focus on deep learning for computer vision (e.g Fashion-Clip)”
The ad says“Familiar with software development practices including version control, CI/CD, containerization, and monitoring for MLOps”
The ad says“Hands-on professional experience in fine-tuning and deploying machine learning solutions end-to-end, with a focus on deep learning for computer vision (e.g Fashion-Clip)”
The ad says“Experience with generative AI systems, prompting, retrieval augmented generation (RAG) and fine tuning LLMs”
The ad says“Proficiency in Python and familiarity with ML/AI libraries (e.g. PyTorch, TensorFlow, Hugging Face) for computer vision.”
The ad says“Experience with generative AI systems, prompting, retrieval augmented generation (RAG) and fine tuning LLMs”
The ad says“Proficiency in Python and familiarity with ML/AI libraries (e.g. PyTorch, TensorFlow, Hugging Face) for computer vision.”
The ad says“Familiar with software development practices including version control, CI/CD, containerization, and monitoring for MLOps”
The ad says“Familiar with software development practices including version control, CI/CD, containerization, and monitoring for MLOps”
The ad says“Experience with generative AI systems, prompting, retrieval augmented generation (RAG) and fine tuning LLMs”
The ad says“Proficiency in Python and familiarity with ML/AI libraries (e.g. PyTorch, TensorFlow, Hugging Face) for computer vision.”
The ad says“Proficiency in Python and familiarity with ML/AI libraries (e.g. PyTorch, TensorFlow, Hugging Face) for computer vision.”
The ad says“Experience with generative AI systems, prompting, retrieval augmented generation (RAG) and fine tuning LLMs”
The ad says“Proficiency in Python and familiarity with ML/AI libraries (e.g. PyTorch, TensorFlow, Hugging Face) for computer vision.”
The ad says“Familiar with software development practices including version control, CI/CD, containerization, and monitoring for MLOps”

Company Description

At ASOS, we’re reimagining the future of fashion content and digital experiences. As we accelerate our global growth, Studios sits at the heart of this transformation delivering the high-quality imagery and video that power every customer interaction. Backed by significant investment in cutting-edge technology, AI-driven content creation, and cloud-native platforms, we’re evolving from traditional shoot-led production to a scalable, data-driven content engine enabling faster speed to market, richer personalisation, and truly immersive shopping experiences. This is a unique opportunity to shape how millions of customers discover and engage with fashion, as part of a team pushing the boundaries of creativity, technology, and innovation every day.

Job Description

What you’ll be doing

As a Senior AI Engineer, you’ll help build and scale AI‑driven solutions that power asos Studios and deliver images and videos to millions of ASOS customers. This role focuses on designing reliable, responsible and high‑performing AI systems, using Deep learning embedding techniques for multimodal signal processing, and generative AI technologies such as large language models (LLMs).

You’ll work closely with Studios, Machine Learning Engineers and Product teams to shape the next generation of AI-powered automation for ASOS Studios. By applying computer vision to product imagery and external visual inspiration, you’ll uncover rich styling signals and combine them with customer insights to create smarter image generation, more engaging shopping journeys and more personalised fashion experiences.

Designing and developing AI solutions using LLMs and generative AI, including iterating on prompts and workflows to improve output quality

Building and maintaining scalable data pipelines, applying best practices in data preparation to ensure quality and reliability

Helping to standardise and reuse AI workflows, making it easier for teams across different domains to build consistently and efficiently

Applying MLOps principles to AI systems, including CI/CD, monitoring, model management and feature governance

Partnering with Cloud Infrastructure teams to design secure, cost‑effective environments for AI workloads

Embedding ethical and responsible AI practices into development, proactively identifying and mitigating bias and risk

Fine‑tuning pre‑trained models for specific use cases to improve relevance and performance

Designing and contributing to evaluation frameworks for AI models, including automated testing and benchmarking to support ongoing improvement

Qualifications

Key Skills and Experience

Proficiency in Python and familiarity with ML/AI libraries (e.g. PyTorch, TensorFlow, Hugging Face) for computer vision.

Hands-on professional experience in fine-tuning and deploying machine learning solutions end-to-end, with a focus on deep learning for computer vision (e.g Fashion-Clip)

Experience with generative AI systems, prompting, retrieval augmented generation (RAG) and fine tuning LLMs

Familiar with software development practices including version control, CI/CD, containerization, and monitoring for MLOps

Experience in taking projects from inception to production.

A collaborative mindset with strong communication skills and the ability to work effectively across multidisciplinary teams.

Motivated self-starter with a desire to learn, share knowledge, and grow in a fast-paced environment.

Additional Information

BeneFITS’

Employee discount (hello ASOS discount!)
Employee sample sales
25 days paid annual leave + an extra celebration day for a special moment
Discretionary bonus scheme
Private medical care scheme
Flexible benefits allowance - which you can choose to take as extra cash, or use towards other benefits
Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role