Senior MLOps Engineer 15722

Veritaz is a leading IT staffing solutions provider in Sweden, committed to advancing individual careers and aiding employers in ensuring the perfect talent fit. With a proven track record of successful partnerships with top companies, we have rapidly grown our presence in the USA, Europe, and Sweden as a dependable and trusted resource within the IT industry.

Assignment Description

We are looking for a Machine Learning Engineer (Mid–Senior level)

What you will work on

• Build and operate machine-learning–based recommendation and personalization systems
• Develop end-to-end ML pipelines including data processing, feature engineering, and model orchestration
• Design, deploy, and monitor ML models in production environments
• Build and maintain high-availability, customer-facing APIs
• Work with MLOps tooling on GCP, including Vertex AI Pipelines or Kubeflow Pipelines
• Manage and optimize data workflows using BigQuery, SQL, and DBT
• Implement infrastructure as code and manage cloud resources securely
• Collaborate closely with data scientists, engineers, and product teams
• Ensure high code quality through testing, code reviews, and engineering best practices
• Continuously improve performance, scalability, and reliability of ML systems

What you bring

Mandatory requirements

GCP & MLOps

• Experience with Vertex AI Pipelines or Kubeflow Pipelines
• Experience working with BigQuery
• Advanced SQL skills
• Experience with Cloud Composer or Airflow
• Experience with IAM, service accounts, and cloud security configuration
• Experience with Data Catalog
• Understanding of Infrastructure as Code (e.g. Terraform or similar tools)

Python & engineering practices

• Deep knowledge of Python programming and object-oriented design
• Experience following coding best practices (flake8, mypy, black, SonarQube, pre-commit)
• Strong experience with unit testing and end-to-end testing (Pytest, fixtures, unittest)

Data engineering

• Deep knowledge of DBT (preferably on GCP)
• Strong SQL skills
• Solid understanding of data modeling and system design

DevOps / platform

• Proficiency with Unix-based systems
• Ability to install and configure components in Docker environments
• Strong shell scripting skills
• Experience with Git (PRs, code reviews, merge conflict resolution)
• Experience building CI/CD pipelines (e.g. GitHub Actions)
• Deep understanding of Docker

Soft skills

• Strong problem-solving mindset and ability to learn new technologies quickly
• Proactive and structured approach to complex challenges
• Strong communication skills with both technical and non-technical stakeholders
• Enjoys giving and receiving constructive code review feedback
• Comfortable working in teams operating high-availability, customer-facing systems