Ml Platform Engineer (Ai)

TL;DR

Ml Platform Engineer (AI): Architecting and evolving scalable, reliable ML infrastructure including GPU-dense clusters, hybrid cloud/on-prem systems, and high-throughput pipelines for multimodal AI model training and deployment with an accent on compute orchestration, automation, and hybrid cloud strategies. Focus on designing large-scale distributed systems, ensuring reproducibility, and optimizing performance for cutting-edge oncology AI applications.

Location: Based in The Netherlands or Switzerland with at least 50% onsite presence

Company

hirify.global builds AI assistants for oncology in collaboration with leading cancer research institutes, focusing on multimodal AI to support clinicians.

What you will do

• Architect, scale, and evolve ML infrastructure from IaC to CI/CD and container orchestration.
• Advance compute orchestration layers to scale GPU and CPU workloads using Kubernetes and scheduling strategies.
• Design hybrid and multi-cloud strategies balancing performance, compliance, and cost.
• Build automation and validation pipelines ensuring reproducible and optimized training environments.

Requirements

• Location: Must be based in The Netherlands or Switzerland with hybrid work (50% onsite)
• Expertise in Kubernetes, SLURM, Helm, Terraform, and container ecosystems.
• Experience with CI/CD tools like ArgoCD, GitHub Actions.
• Proficiency in systems programming languages such as Python, Go, or Rust.
• Knowledge of observability tools like Prometheus, Grafana, Loki.
• Familiarity with ML infrastructure tools like Ray, MLFlow, NVIDIA GPU training stack.

Nice to have

• Experience with data orchestration tools like Airflow, Dagster, Prefect, Flyte.
• Knowledge of distributed storage systems such as VAST, Weka, Hammerspace, or S3.

Culture & Benefits

• Competitive salary, pension plan, and 25 vacation days per year.
• EUR 1000 learning and development budget.
• Autonomy in work style and flexible schedules.
• Annual commuting subsidy and team events.