Senior Machine Learning Engineer

Avaron AB is a growing consultancy focused on technology, finance, and business support. We match your expertise with the market's most interesting assignments, offering a platform where your professional development is central.

You will join a team building customer-facing machine learning solutions, with a focus on recommendation and personalization. The environment is strongly oriented around Google Cloud Platform and production-grade data/ML pipelines, with an emphasis on code quality, automation, and scalable system design.

• Design, build, and maintain ML pipelines using Vertex AI pipelines / Kubeflow
• Develop and optimize data workflows using BigQuery and SQL
• Orchestrate pipelines with Cloud Composer / Airflow
• Work with IAM and service accounts to enable secure access patterns
• Use and maintain metadata through Data Catalog
• Apply Infrastructure as Code principles in the platform setup and evolution
• Develop Python code following best practices (OOP, linting, typing, formatting, and static analysis)
• Write and maintain unit and end-to-end tests using established Python testing frameworks
• Collaborate via Git workflows (PRs, code reviews, and merge conflict resolution)
• Build and maintain CI/CD pipelines (e.g., GitHub Actions)
• Work with Docker-based development and runtime environments
• Contribute to data modeling and system design for robust, scalable solutions

• Strong experience in Python development, including OOP and coding best practices
• Experience with flake8, mypy, black, SonarQube, and pre-commit
• Strong testing experience (unit and end-to-end), using tools such as Pytest/fixtures/unittest
• Solid experience with SQL and BigQuery
• Hands-on experience with Vertex AI pipelines / Kubeflow pipelines
• Experience with Cloud Composer / Airflow
• Understanding of IAM and service accounts
• Experience working with Data Catalog
• Understanding of Infrastructure as Code concepts
• Deep understanding of Docker and Unix environments, including shell usage
• Strong Git skills (PR workflow and merge conflict handling)
• Ability to create CI/CD pipelines (e.g., GitHub Actions) using best practices
• Strong understanding of data modeling and system design

• Experience with Dataflow
• Experience with Kubernetes
• Experience building high-availability APIs
• Experience with ML-based recommendations and personalization systems
• Strong DBT experience, preferably in a GCP context

Selections are made on an ongoing basis, so we recommend that you apply as soon as possible.