Senior Mlops/Ml Platform Engineer

TL;DR

Senior MLOps/ML Platform Engineer: Designing, building, and operationalizing ML solutions for a European fashion and retail company, focusing on platform-level evaluation, implementation, and early production rollout. Focus on integrating ML platform tools and infrastructure into a shared, scalable platform, ensuring reliability, security, and performance of ML systems in production.

Location: Other, Central Europe

Company

hirify.global is an outsourcing company.

What you will do

• Design, build, and validate ML platform POCs across multiple use cases.
• Collaborate with Applied Scientists, ML Engineers, and Platform teams to deliver end-to-end ML workflows.
• Implement and operate ML pipelines for training, inference, deployment, and monitoring.
• Optimize ML workloads on Kubernetes, including GPU-based and multi-tenant environments.
• Define best practices, governance, and onboarding standards for teams adopting the platform.
• Ensure reliability, security, and performance of ML systems in production.

Requirements

• Strong experience building and operating production-grade ML platforms or large-scale data/ML systems on cloud infrastructure.
• Solid background in distributed systems, including containers (Docker), orchestration (Kubernetes), and streaming / batch processing (Kafka, Spark, Flink, etc.).
• Experience designing and operating scalable, low-latency, or high-throughput systems.
• Strong understanding of reliability, monitoring, and safe deployment practices (SLOs, incident response, capacity planning).
• Experience embedding security, IAM, and governance into platform workflows.
• Strong communication skills, with the ability to produce architecture designs, POC findings, and technical recommendations.

Nice to have

• Experience with Kubernetes-first ML systems, including running ML workloads on Kubernetes (EKS preferred).
• Experience with enterprise ML platforms (e.g. Databricks, Domino, ClearML).
• Experience with feature platforms / feature stores (Feast, Hopsworks, etc.).
• Familiarity with governance and compliance in regulated ML environments.
• Focus on developer experience and platform enablement (templates, golden paths, onboarding flows).

Culture & Benefits

• Paid Vacation
• Sick Days
• Floating Holidays
• Sport/Insurance Compensation
• English Classes
• Charity
• Training Compensation