4 days ago
London, United KingdomSenior
Responsibilities
- Design, build, deploy, and operate production machine learning systems for outfit discovery and personalised fashion experiences.
- Partner with Machine Learning Scientists to deploy and optimise deep learning models serving millions of customers.
- Build and improve recommendation, retrieval, ranking, personalisation, and AI-driven fashion discovery systems.
- Improve performance, reliability, observability, and scalability across the machine learning lifecycle.
- Contribute to technical designs, architecture discussions, engineering practices, and shared machine learning capabilities.
- Mentor and support engineers through coaching, collaboration, and knowledge sharing.
- Work with cross-functional product teams to deliver customer and business outcomes.
Requirements
- Experience designing, building, and deploying machine learning systems in production.
- Strong understanding of machine learning engineering principles and modern software engineering practices.
- Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow, or similar.
- Experience training and optimising models using large datasets and distributed compute infrastructure.
- Experience with recommendation systems, ranking, retrieval, personalisation, or related machine learning domains.
- Knowledge of MLOps practices, including model deployment, monitoring, and lifecycle management.
- Experience building reliable, observable, and scalable services in cloud environments.
- Experience providing technical leadership and mentoring other engineers.
- Strong collaboration and communication skills in cross-functional product teams.
- Curiosity about emerging AI technologies and practical applications of LLMs and generative AI in customer-facing products.
Benefits
- Employee discount and access to employee sample sales.
- 25 days of paid annual leave plus an extra celebration day.
- Discretionary bonus scheme.
- Private medical care scheme.
- Flexible benefits allowance that can be taken as extra cash or used toward other benefits.
- Personalised learning and in-the-moment development experiences.
Tech Stack
PyTorchTensorFlow
Categories
