Senior ML Ops Engineer

#BETHEDIFFERENCE

If making a difference matters to you, then you matter to us.

Join us, at Wolters Kluwer, and be part of a dynamic global technology company that makes a difference every day. We’re innovators with impact. We provide expert software & information solutions that the world’s leading professionals rely on, in the moments that matter most.

You’ll be supported by collaborative colleagues who share a purpose. We are 21,000 people unique in our dreams, life stories, abilities, and passions who come together every day with one ambition: to make a difference.​ We do our best work together, connecting to create new innovations with impact.

Job Description

We are looking for an experienced software engineer specialized in Machine Learning Ops to join our team in Cluj Napoca, Romania.

This person will have the following responsibilities: 

• Improve and maintain the IaC pipelines of the machine learning platform in the cloud, both for the training and serving infrastructure. Keep a global view on reusable infrastructure components across different ML systems 

• Contribute to transversal improvements for the ML platform, tackling topics such as authentication (RBAC, AAD), networking, logging improvements or disaster recovery 

• Occasionally contribute to the development of web APIs to expose ML models as services 

• Work with machine learning engineers to solve engineering problems related to ML systems, such as optimizing training costs, or improving inference latency 

• Collaborate with other engineering teams to integrate the ML Platform in the larger multi-tenant SaaS roadmap of the company 

The team 

The Datalab team is responsible for designing, developing and maintaining AI-powered products at Enablon, to improve worker safety, enhance operational processes or reduce environmental impact. The team is composed of engineers with a diverse skill-set (machine learning engineers, full-stack web developers, quality engineers), and takes ownership for the full lifecycle of machine learning systems, from model training to deployment and monitoring in production. 

We work with the following tech stack: 

• Programming languages: mainly Python, .NET for specific components 

• Cloud: Azure services such as 

• Machine Learning: Azure Machine Learning, Azure Cognitive Service 

• Web development: Azure Functions, Azure App service 

• Storage: Azure Blob storage, Azure CosmosDB, SQL Server 

• Infrastructure-as-code: Pulumi or Terraform 

• CI/CD pipelines: GitHub Actions

Qualifications 

• 5+ years of experience working as a software engineer, some of which in the field of <