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8 дней назад

Machine Learning Engineer (AI)

Формат работы
onsite
Тип работы
fulltime
Английский
b2
Страна
UK
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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TL;DR
Machine Learning Engineer (AI) (Recommender Systems/MLOps): Building and operating production-grade machine learning systems for personalised recommendations, product ranking, and AI-powered styling at ASOS with an accent on real-time personalisation, scalable model deployment, and customer behaviour signals. Focus on developing ranking models, deploying batch and real-time services, monitoring production performance, and improving shared MLOps capabilities.

Location: hirify.global HQ in London, with an office in Leavesden

Company

hirify.global is an online fashion retailer using technology, data, and innovation to help customers discover and shop for products.

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.
  • Collaborate with Applied Scientists, Software Engineers, and Product partners to move models from experimentation into production.
  • Monitor, evaluate, and iterate on models using customer behaviour and performance metrics.
  • Contribute to MLOps tooling, engineering standards, and shared machine learning platform capabilities.

Requirements

  • Experience developing, deploying, or operating machine learning solutions in production.
  • Familiarity with machine learning frameworks and tools such as PyTorch, TensorFlow, or XGBoost.
  • Experience training models with 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, matched pension contributions of 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.
  • Free shuttle bus between Watford station and the Leavesden office.

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