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7 дней назад

London - ML Ops Engineer II (Experiences)

Формат работы
hybrid
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
UK
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
London - ML Ops Engineer II (Experiences) (AWS/ML Platforms): Building and maintaining scalable infrastructure for pre-computed, batch, and real-time machine learning models with an accent on cloud platforms, model lifecycle support, and reliable deployment. Focus on monitoring ML pipelines, developing infrastructure as code, supporting high-throughput and low-latency workloads, and enabling data science teams to deliver AI products.

Location: Hybrid role based in London, United Kingdom; candidates must already be based in London or within a maximum 1.5-hour commute. Office attendance is approximately twice per month.

Company

hirify.global, part of Tripadvisor, operates a global marketplace for travel experiences and uses technology, AI, machine learning, and data science to connect travelers with experiences.

What you will do

  • Provide tools, infrastructure, and support for data science and machine learning stakeholders.
  • Develop and evolve the MLOps technology stack in AWS cloud environments.
  • Build and maintain scalable infrastructure for pre-computed, batch, and real-time model workloads.
  • Own software engineering activities from design and implementation through QA, monitoring, and maintenance.
  • Monitor ML pipelines for accuracy, drift, enhancements, SLA compliance, and billing volumes.
  • Define and document requirements with cross-functional stakeholders for ML and AI products.

Requirements

  • At least 2 years of MLOps experience building infrastructure across the machine learning model lifecycle.
  • Hands-on experience with AWS and/or GCP.
  • Experience with infrastructure-as-code tools such as Terraform or CloudFormation.
  • Experience with CI/CD processes and platforms.
  • Ability to work across diverse technologies and collaborate effectively in cross-functional teams.
  • Strong verbal and written communication, ownership, urgency, and attention to quality.

Nice to have

  • Experience with Kubernetes, Seldon, KServe, Ray Serve, MLflow, SageMaker, Kubeflow, Argo CD, Docker, Python, Java, Ray, Spark, Pandas, PostgreSQL, Snowflake, or BigQuery.
  • Knowledge of vector or graph databases.
  • Experience optimizing models for high throughput, low latency, and cost efficiency.
  • Experience with LLMOps and open-source models.

Culture & Benefits

  • Remote-friendly collaboration with flexible working arrangements and the option to work onsite in select locations.
  • Flexible schedule designed to support work-life balance.
  • Competitive compensation including base salary, annual bonus, and equity.
  • Health benefits, employee assistance, donation matching, tuition assistance, and an annual lifestyle benefit.
  • Travel discounts and an inclusive workplace focused on curiosity, collaboration, customer service, and continuous improvement.

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