Senior AI Engineer – Machine Learning (Computer Vision)
ASOS is hiring a Senior AI Engineer – Machine Learning (Computer Vision) for a remote role open to applicants in United Kingdom. Level rates it ; you can apply on ASOS.
Level's read on this job
- Level rates this AI engineer role Builds AI ●●●●: the job is building AI systems.
- This is listed as a remote role.
- The posting mentions Hugging Face, PyTorch and TensorFlow among its tools and skills.
- Level classes it as a senior role.
- ASOS has 66 other open roles on Level.
AI in this role
Design and scale computer vision and generative AI solutions powering fashion e-commerce experiences.
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.
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
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.
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
How we rate this
Senior AI Engineer – Machine Learning (Computer Vision) at ASOS rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- Typical AI engineer job
- $182k
This posting doesn't list pay. Use the typical AI engineer figure when pay comes up. See AI engineer jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Walk me through a computer vision problem you solved, from raw data to a deployed model.
- How do you think about the risk of an AI system in this kind of role failing silently?
Adapt your resume
- List these exact terms on your resume: RAG, Fine-tuning, ML Ops, Computer vision, and AI Safety. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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