Senior AI Engineer – Machine Learning (Computer Vision)

ASOS.com; Greater London; On-site; GBP 70,000 - 120,000; Full time

Benefits offered by this job

Employee discount (ASOS)

Employee sample sales

25 days paid annual leave + extra day

Discretionary bonus scheme

Private medical care scheme

Flexible benefits allowance

Learning and development opportunities

Job summary

ASOS Studios is building a scalable, AI-powered content engine to accelerate imagery and video production for millions of customers. The Senior AI Engineer will design reliable AI systems, apply multimodal signal processing, and leverage generative AI technologies to optimise fashion content and personalisation.

You’ll collaborate with Studios, ML Engineers and Product teams to deploy end-to-end AI workflows, ensure governance, and drive continuous improvement in production-ready solutions.

Qualifications

• Proficiency in Python and ML/AI libraries for computer vision.
• Hands-on experience fine-tuning and deploying ML solutions end-to-end, with deep learning focus.
• Experience with generative AI systems, prompting, RAG and LLMs.
• Familiarity with software development practices including version control, CI/CD, containers, monitoring for MLOps.
• Experience taking projects from inception to production.
• Collaborative mindset with strong communication skills across teams.
• Self-starter with a desire to learn in a fast-paced environment.

Responsibilities

• Design and develop AI solutions using LLMs and generative AI, iterating on prompts and workflows to improve output quality.
• Build and maintain scalable data pipelines with high data quality and reliability.
• Standardise and reuse AI workflows across domains for efficiency and consistency.
• Apply MLOps principles to AI systems: CI/CD, monitoring, model management, feature governance.
• Collaborate with Cloud Infrastructure to create secure, cost-effective AI environments.
• Embed ethical and responsible AI practices; proactively identify bias and risk.
• Fine-tune pre-trained models for specific use cases to improve relevance and performance.
• Contribute to evaluation frameworks with automated testing and benchmarking for continuous improvement.

Skills

Python

PyTorch

TensorFlow

Hugging Face

LLMs

RAG

MLOps

ML pipelines

Multimodal signals

Tools

Docker

Kubernetes

CI/CD

AWS

MLflow

Job 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 aSenior 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