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A leading online fashion retailer is looking for a Senior AI Engineer to innovate and scale AI-driven solutions for enhancing customer experiences. You will work with various teams to deliver ethical and high-performing AI systems, leveraging LLMs and generative AI. Candidates must have a strong background in AI engineering, proficiency in Python, and hands-on experience with tools like PyTorch and TensorFlow. The role offers exciting opportunities for professional growth and a range of employee benefits including discounts and a robust medical care scheme.
We’re ASOS, the online retailer for fashion lovers all around the world.
We exist to give our customers the confidence to be whoever they want to be, and that goes for our people too. At ASOS, you’re free to be your true self without judgement, and channel your creativity into a platform used by millions.
But how are we showing up? We’re proud members of Inclusive Companies, are Disability Confident Committed and have signed the Business in the Community Race at Work Charter and we placed 8th in the Inclusive Top 50 Companies Employer list.
Everyone needs some help showing up as their best self. Let our Talent team know if you need any adjustments throughout the process in whatever way works best for you.
As a Senior AI Engineer, you’ll focus on building and scaling AI-driven solutions that power personalised experiences for millions of ASOS customers. You’ll design and implement robust AI systems leveraging LLMs, generative AI, and advanced data pipelines, ensuring ethical, secure, and high-performing solutions.
You’ll collaborate closely with Applied Scientists, ML Engineers, and Product teams to accelerate delivery and improve the quality of AI systems by providing reusable templates, prompt engineering strategies, and infrastructure that supports experimentation.
Professional experience as an AI Engineer or similar role, with strong exposure to LLMs and generative AI.
Solid understanding of the end-to-end AI lifecycle, from experimentation through deployment and monitoring.
Proficiency in Python and familiarity with ML/AI libraries (e.g., PyTorch, TensorFlow, Hugging Face).
Experience with prompt engineering and optimisation for generative AI systems.
Comfortable working with cloud platforms (preferably Azure) and containerisation (Docker/Kubernetes).
Knowledge of MLOps tools and practices such as MLflow, CI/CD pipelines, and model monitoring.
Passionate about ethical AI, bias mitigation, and improving developer experience through automation and tooling.
Experience in fine-tuning large language models and adapting them for specific use cases.
Strong understanding of evaluation methodologies for AI systems, including quantitative and qualitative metrics.
Ability to design automated evaluation pipelines for continuous monitoring and improvement of AI models.