Senior AI Engineer - Computer Vision

Role Overview

As a Senior AI Engineer, you’ll help build and scale AI-driven solutions that deliver images and videos to millions of 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. 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.

Key Responsibilities

1. Design and develop AI solutions using LLMs and generative AI, including iterating on prompts and workflows to improve output quality.
2. Build and maintain scalable data pipelines, applying best practices in data preparation to ensure quality and reliability.
3. Help standardise and reuse AI workflows, making it easier for teams across different domains to build consistently and efficiently.
4. Apply MLOps principles to AI systems, including CI/CD, monitoring, model management and feature governance.
5. Partner with Cloud Infrastructure teams to design secure, cost-effective environments for AI workloads.
6. Embed ethical and responsible AI practices into development, proactively identifying and mitigating bias and risk.
7. Fine-tune pre-trained models for specific use cases to improve relevance and performance.
8. Design and contribute to evaluation frameworks for AI models, including automated testing and benchmarking to support ongoing improvement.

Key Skills and Experience

1. Proficiency in Python and familiarity with ML/AI libraries such as PyTorch, TensorFlow and Hugging Face for computer vision.
2. Hands-on professional experience in fine-tuning and deploying machine learning solutions end-to-end, with a focus on deep learning for computer vision, such as Fashion-CLIP.
3. Experience with generative AI systems, prompting, Retrieval-Augmented Generation (RAG) and fine-tuning LLMs.
4. Familiarity with software development practices including version control, CI/CD, containerization and monitoring for MLOps.
5. Experience in taking projects from inception to production.
6. A collaborative mindset with strong communication skills and the ability to work effectively across multidisciplinary teams.
7. Motivated self-starter with a desire to learn, share knowledge and grow in a fast-paced environment