4 days ago
London, United KingdomMid Level
Responsibilities
- Design, build, and maintain production-grade machine learning systems for personalization and product discovery.
- Develop and improve recommender systems, ranking models, and customer-facing machine learning capabilities.
- Deploy models into batch and real-time environments while ensuring reliability, scalability, and performance.
- Collaborate with Applied Scientists and Engineers to move models from experimentation into robust production systems.
- Monitor, evaluate, and iterate on models using customer behavior and performance metrics.
- Contribute to engineering best practices, MLOps tooling, and shared machine learning platform capabilities.
- Improve how machine learning is developed, deployed, and operated across the organization.
Requirements
- Experience developing, deploying, or operating machine learning solutions in production environments.
- Familiarity with modern machine learning frameworks and tooling such as PyTorch, TensorFlow, or XGBoost.
- Experience training models using GPUs, or an interest in distributed computing and scalable machine learning systems.
- Understanding of software engineering fundamentals including version control, CI/CD, testing, observability, and containerization.
- Appreciation of MLOps practices and the challenges of deploying machine learning systems at scale.
- Strong collaboration and communication skills across engineering, science, and product disciplines.
- Curiosity, adaptability, and enthusiasm for learning new technologies and approaches.
Benefits
- Employee discount and access to employee sample sales.
- 25 days of paid annual leave plus an additional celebration day.
- Private medical care scheme.
- Fixed annual payment in addition to salary.
- Personalized learning and in-the-moment development experiences.
- The posting describes disability adjustment support during the hiring process.
Tech Stack
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