12 hours ago
Copenhagen, DenmarkSenior
Responsibilities
- Design, build, and maintain scalable cloud infrastructure supporting data and ML workloads, primarily on GCP.
- Collaborate with data scientists and engineers to translate research prototypes into robust production systems.
- Design and implement reliable, scalable, observable, and operationally mature data and ML platforms.
- Identify and resolve technical debt, bottlenecks, and inefficiencies across infrastructure and platform components.
- Contribute to CI/CD, version control, testing, automation, and repository maintenance best practices.
- Participate in technical discussions, knowledge sharing, and continuous improvement across the team.
Requirements
- At least 4 years of experience in infrastructure engineering, platform engineering, data engineering, or large-scale software engineering.
- Strong practical experience with Python and SQL.
- Experience designing and operating systems in cloud environments such as GCP, AWS, or Azure.
- Familiarity with ML frameworks such as PyTorch or TensorFlow.
- Familiarity with MLOps tools such as MLflow, Kubeflow, or similar ML platforms.
- Experience with API design, testing best practices, CI/CD, and version control.
- Experience building or supporting large-scale data or ML platforms, cloud platforms, or other scalable production systems.
- Strong interest in reliable, automated platforms supporting AI and data workloads, plus the ability to collaborate across disciplines.
- Familiarity with Spark, Flink, or Airflow is preferred.
- Experience with Docker and ideally Kubernetes is preferred.
- Experience with strongly typed languages such as Java, Go, or C++ is preferred.
- Interest in using AI coding assistants to improve engineering productivity is preferred.
Benefits
- Hybrid Copenhagen role with office attendance approximately four days per week.
- Candidates must currently reside in Denmark or relocate independently; relocation support is not provided.
- Opportunity to work on large-scale global infrastructure and marketing intelligence systems.
- Collaborative, inclusive culture with opportunities for learning, knowledge sharing, and career growth.
- Challenging work with significant scale, influence, and cross-disciplinary collaboration.
Tech Stack
Apache AirflowApache FlinkApache SparkAWSAzureC++DockerGoGoogle Cloud PlatformJavaKubernetesMLflowPythonPyTorchSQLTensorFlow
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