1 week ago

Data & ML Infrastructure Engineer

Optics11

Amsterdam

1 week ago

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Data & ML Infrastructure Engineer needed to own and evolve the data and ML platform for a deep-tech scale-up in Amsterdam. The role involves designing cloud-agnostic infrastructure, ensuring scalability and reliability, and bridging data science and IT teams. Requires 5+ years experience with data platforms, cloud infrastructure, Terraform, Kubernetes, and Python.

AIOn-siteFull-timeSeniorData PlatformsCloud Infrastructure

Data & ML Infrastructure Engineer

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AIOn-siteFull-timeSeniorData Platforms

Salary

Not specified

Work Location

Amsterdam, North Holland, Netherlands, NL

Work Model

On-site

Experience Required

5 years

Employment Type

Full-time

Experience Level

Mid-Senior level

Core Qualifications

Technical (Must-have)

Data platformsCloud infrastructureDistributed systemsAWSGCPAzureTerraformMLflowFeastDVCDataHubAWS SageMakerGoogle Vertex AIMongoDBPostgreSQLInfluxDBApache KafkaRabbitMQDockerKubernetesGitLab CIPythonPrometheusGrafanaDevOpsMLOpsCI/CDInfrastructure-as-CodeContainerization

Preferred Qualifications

Technical (Nice-to-have)

Data governanceIAMSecurity frameworksCost optimizationResource managementMulti-tenant architectures

Key Responsibilities

•Design, implement, and maintain the data and ML platform infrastructure, including data ingestion, storage, processing, and training systems.
•Ensure high availability, reliability, and uptime of the platform.
•Maintain and evolve vendor-delivered platform components.
•Build and maintain data workflows, including dataset versioning, experiment tracking, and model lifecycle management.
•Enforce DevOps / MLOps practices, including CI/CD pipelines and Infrastructure-as-Code.
•Develop cloud-agnostic and containerized solutions for public and private cloud environments.
•Optimize data storage, lifecycle policies, and cost efficiency.
•Implement and maintain monitoring and alerting systems (Prometheus, Grafana).
•Ensure data governance, security, and compliance (access control, audit logging, anonymization).
•Collaborate with data scientists, ML engineers, and IT teams.
•Manage resource and cost controls.
•Contribute to documentation, operational runbooks, and onboarding materials.

Data & ML Infrastructure EngineerOn-siteAmsterdamML platformCloud infrastructureKubernetesTerraformPythonDeep-tech

Key Responsibilities

•Design, implement, and maintain the data and ML platform infrastructure, including data ingestion, storage, processing, and training systems.

•Ensure high availability, reliability, and uptime of the platform.

•Maintain and evolve vendor-delivered platform components.

•Build and maintain data workflows, including dataset versioning, experiment tracking, and model lifecycle management.

•Enforce DevOps / MLOps practices, including CI/CD pipelines and Infrastructure-as-Code.

•Develop cloud-agnostic and containerized solutions for public and private cloud environments.

•Optimize data storage, lifecycle policies, and cost efficiency.

•Implement and maintain monitoring and alerting systems (Prometheus, Grafana).

•Ensure data governance, security, and compliance (access control, audit logging, anonymization).

•Collaborate with data scientists, ML engineers, and IT teams.

•Manage resource and cost controls.

•Contribute to documentation, operational runbooks, and onboarding materials.