9 дней назад
Machine Learning Engineer (Recommendations)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Machine Learning Engineer (Recommendations): Building and operating production-grade recommender systems, ranking models, and AI-powered styling experiences for ASOS with an accent on personalisation, real-time customer behaviour signals, and scalable deployment. Focus on developing batch and real-time machine learning systems, monitoring model performance, and improving MLOps practices across the organisation.
Location: London, United Kingdom
Company
is an online fashion retailer building digital shopping experiences for customers worldwide.
What you will do
- Design, build, and maintain production-grade machine learning systems for personalisation and product discovery.
- Develop and improve recommender systems, ranking models, and customer-facing machine learning capabilities.
- Deploy models in batch and real-time environments with a focus on reliability, scalability, and performance.
- Work with Applied Scientists, Software Engineers, and Product partners to move models from experimentation into production.
- Monitor and evaluate models using customer behaviour and performance metrics, then iterate on their effectiveness.
- Contribute to MLOps tooling, engineering best practices, and shared machine learning platform capabilities.
Requirements
- Experience developing, deploying, or operating machine learning solutions in production.
- 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 containerisation.
- 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.
Culture & Benefits
- Employee discount and access to employee sample sales.
- 25 days of paid annual leave plus an additional celebration day.
- Private medical care, pension contributions matched up to 5%, and a discretionary bonus scheme.
- Personalised learning and career development opportunities.
- Summer hours with 3pm finishes on Fridays during June, July, and August.
- Access to London office facilities, including a gym, subsidised canteen, café, and shuttlebus service for the Leavesden office.
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