mlops engineer

The company is a fast-growing AI infrastructure scale-up based in Helsinki that develops cloud platforms for production AI systems.

• Design and build scalable machine learning platforms for production environments;
• Develop automated model training, deployment, and monitoring pipelines;
• Support machine learning engineers with reliable self-service infrastructure and tooling;
• Build Infrastructure as Code and deployment automation for cloud-native AI platforms;
• Improve observability, reliability, and operational performance across ML systems;
• Optimize model serving, inference performance, and platform scalability;
• Collaborate with software, data, and platform engineers to continuously improve the AI development lifecycle.

• 4+ Years of experience in Platform Engineering, MLOps, DevOps, Cloud Engineering, or Machine Learning Infrastructure;
• Strong Python development and automation skills;
• Hands-on experience with Kubernetes and containerized production environments;
• Experience supporting machine learning workloads in cloud environments;
• Strong understanding of Infrastructure as Code using Terraform or similar tools;
• Experience building CI/CD pipelines and cloud-native platforms;
• Nice to have: Experience supporting Large Language Models or Generative AI platforms, NVIDIA GPU infrastructure and CUDA optimization, vector databases and Retrieval-Augmented Generation (RAG) architectures, Ray, Airflow, Feast, or feature store technologies, Prometheus, Grafana, OpenTelemetry, or Datadog, experience with distributed training and high-performance inference systems.

• Fully remote role open across the European Union;
• Opportunity to work with cutting-edge cloud-native and machine learning technologies;
• High level of ownership with opportunities to influence platform architecture and engineering standards;
• Collaboration with experienced AI, platform, and cloud engineers;
• Long-term career progression within a company investing in AI infrastructure.