Senior Machine Learning Engineer

Om jobbet

About the Company

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.

About the Assignment

You will join a team building and operating customer-facing recommendation and personalization solutions. The environment is centered around Google Cloud Platform (GCP) and modern data/ML engineering practices, with a strong focus on reliable pipelines, high code quality, and scalable delivery.

Job DescriptionDevelop and maintain ML/data pipelines using Vertex AI pipelines/Kubeflow and orchestration tooling (Cloud Composer/Airflow).

Work with BigQuery and write efficient SQL to support analytics and ML use cases.

Build and maintain Python codebases with strong engineering standards (OOP, linting/type checks, testing, and CI/CD).

Collaborate with stakeholders and engineers to design robust data models and system designs.

Contribute to code reviews and continuous improvement of engineering practices.

Manage access and permissions in GCP (IAM, service accounts) and use Data Catalog where relevant.

Support infrastructure and deployment practices aligned with Infrastructure as Code principles.

RequirementsHands-on experience with GCP, including Vertex AI pipelines/Kubeflow pipelines.

Experience with BigQuery and strong SQL skills.

Experience with Cloud Composer/Airflow.

Experience with IAM and service accounts.

Experience with Data Catalog.

Understanding of Infrastructure as Code concepts.

Strong Python skills, including OOP and best practices.

Experience with code quality tooling such as flake8, mypy, black, SonarQube, and pre-commit.

Strong testing practices (unit and end-to-end) and familiarity with Pytest, fixtures, and unittest.

Deep understanding of dbt (preferably in a GCP context).

Good Unix and shell skills.

Git proficiency (PR workflow and resolving merge conflicts).

Ability to create CI/CD pipelines using GitHub Actions.

Strong Docker knowledge.

Understanding of data modeling and system design.

Nice to haveExperience with Dataflow.

Experience with Kubernetes.

Experience building high-availability APIs.

Background in machine learning-based recommendation systems and personalization.

Application

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