Lead Platform Engineer Cloud & MLOps

Holisticon Connect is a division within NEXER GROUP, a custom software development company started in Poland in 2017 with a team of over 140 people. The company works with world-renowned brands from Scandinavia, the UK, and Western Europe. The role involves designing and evolving a cloud-native platform supporting large-scale machine learning workflows in the medical imaging domain, focusing on scalable, secure, and production-grade infrastructure across AWS and Kubernetes.

• At least 5 years of professional experience in Platform Engineering, DevOps, or similar roles.
• Hands-on, production experience with Kubernetes (EKS/GKE/AKS), including upgrades, autoscaling, networking, RBAC, and reliability.
• Practical experience building and operating Kubeflow Pipelines or similar for scalable and reproducible ML workflows.
• Strong experience with AWS services (EKS, EC2, S3, IAM, CloudWatch) and ability to design secure and cost-efficient architectures.
• Strong skills in Infrastructure as Code (Terraform) and Git-based workflows.
• Experience with CI/CD pipelines (e.g., GitHub Actions, GitLab CI, Jenkins), including artifact management and environment promotion.
• Solid Python and/or shell scripting skills for automation and platform tooling.
• Experience implementing observability (logging, metrics, tracing) with tools like Prometheus, Grafana, or CloudWatch.
• Security-first mindset with understanding of best practices in access control, secrets management, and infrastructure security.
• Strong Linux/Unix fundamentals.

Nice to have:

• Experience with ML platform tooling (e.g., MLflow, Feast, Argo, Airflow, Ray) and model versioning/monitoring.
• Familiarity with large-scale data processing, especially image data (e.g., digital pathology, whole-slide images).
• Experience with high-performance pipelines, including tuning concurrency, memory usage, and GPU/accelerator integration.
• Knowledge of networking and cloud architecture (VPC design, ingress/egress, service mesh, IAM, policy as code).
• Experience with object storage and artifact management (e.g., S3, registries).
• Exposure to SQL/NoSQL databases.
• Experience working in a regulated environment (e.g., healthcare, pharma, GxP).
• Basic knowledge of JavaScript/TypeScript for internal tools or dashboards.

• Take ownership of designing and evolving a cloud-native platform for large-scale machine learning workflows.
• Shape and operate scalable, secure, and production-grade infrastructure across AWS and Kubernetes.
• Build and optimize ML platforms and pipelines (e.g., Kubeflow).
• Drive infrastructure-as-code, CI/CD, and automation standards.
• Collaborate with product engineers, data scientists, and imaging teams to translate scientific requirements into robust, reliable systems at scale.
• Lead technical initiatives, communicate trade-offs clearly, and collaborate effectively with engineering and data teams.