Senior MLOps Engineer 15722

Om jobbet

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