10 дней назад
Senior ML Ops Engineer (Experiences)
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
Senior ML Ops Engineer (Experiences) (Machine Learning): Building and scaling infrastructure for pre-computed, batch, and real-time machine learning models with an accent on model lifecycle management, cloud platforms, and developer productivity. Focus on migrating ML infrastructure to AWS, designing reliable deployment and monitoring systems, and solving complex scalability challenges across diverse technology stacks.
Location: UK; hybrid role based in the London office, with a minimum of two office visits per month. Candidates must be based in London or within 1.5 hours of London.
Company
Viator, a company, operates a marketplace for more than 300,000 travel experiences.
What you will do
- Provide tools and infrastructure that improve the productivity of Data Science and Machine Learning teams.
- Develop across the existing technology stack and contribute to migration into the AWS cloud.
- Design, build, and maintain scalable infrastructure for pre-computed, batch, and real-time machine learning models.
- Support reliable deployment, operation, and monitoring throughout the machine learning model lifecycle.
- Generate and promote new ideas in ML Ops while solving complex infrastructure problems.
- Collaborate with Data Science, Machine Learning, and cross-functional teams in a fast-paced environment.
Requirements
- 4+ years of ML Ops experience building infrastructure for model development, deployment, management, and monitoring.
- Hands-on experience with AWS and GCP, plus cloud-based data engineering experience.
- Experience with Infrastructure as Code tools such as Terraform and CloudFormation.
- Experience with CI/CD processes and platforms.
- Ability to work across a diverse technology stack, solve complex problems, and adopt new technologies.
- Strong verbal and written communication skills, with the ability to work independently and collaboratively.
Nice to have
- Experience with Python, Spark, Pandas, Docker, Kubernetes, Seldon, MLflow, SageMaker, Valohai, ArgoCD, Argo Workflows, Postgres, BigQuery, or Java.
Culture & Benefits
- Remote-friendly collaboration with flexibility to work on-site in select locations.
- Flexible scheduling designed to support work-life balance.
- Competitive compensation package including base salary, annual bonus, and equity.
- Health benefits, employee assistance, donation matching, tuition assistance, and an annual lifestyle benefit.
- Travel discounts and an environment focused on curiosity, collaboration, inclusion, and continuous improvement.
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