DevOps Engineer

Quick Facts

• Own the infrastructure for processing and ML pipelines on-prem
• Build reliability at scale: scheduling, queues, retries, resource sharing
• Containerize jobs (including GPU) and automate server setup with infrastructure as code
• Provide CI/CD and observability (monitoring + alerting)

Description

You will own the platform that runs processing and ML pipelines, supporting tools developers and ML engineers as workloads scale. Responsibilities include evolving the infrastructure into a distributed setup with job scheduling across CPU/GPU machines, containerizing processing jobs for reliable execution, and automating environments as code. You will also build CI/CD and implement monitoring and alerting to catch failed jobs, full storage, and idle machines early.

Responsibilities

• Own production infrastructure for processing and ML pipelines and act as the first point of contact when issues occur
• Support pipeline execution, scaling, and debugging for other engineering teams
• Improve scheduling and execution (CPU/GPU distribution, queues, retries, resource sharing)
• Containerize processing jobs and run them reliably, including on GPU machines
• Automate server and environment configuration using infrastructure as code
• Build and maintain CI/CD for internal tooling and ML code
• Set up monitoring and alerting for failed jobs, storage capacity, and idle compute
• Optimize compute and storage utilization and coordinate capacity planning
• Identify infrastructure bottlenecks, propose improvements, and drive implementation

Requirements

• 2+ years of hands-on DevOps, SRE, or platform engineering experience
• Experience owning production infrastructure
• Strong Linux skills and scripting in Python and Bash
• Docker and CI/CD experience (GitHub Actions, GitLab CI, or similar)
• Experience with batch or distributed workloads (Kubernetes, Slurm, Nomad, Ray, or similar)
• Configuration management / infrastructure as code (Ansible, Terraform, or similar)
• Large-scale storage experience (NAS, Ceph, MinIO, or similar)
• Monitoring and logging experience (Prometheus, Grafana, or similar)
• Efficiency-minded approach to reduce idle machines and wasted storage
• Ownership mindset—take responsibility when systems break
• Supportive attitude toward enabling other engineers
• Comfort working with AI coding tools
• Communicative English

Benefits

• Ownership of infrastructure behind an ambitious project with major technology companies
• Work with experienced motion specialists and ML engineers
• Hybrid work from the studio at Strażacka 53, Warsaw
• Employment contract (umowa o pracę) or alternative arrangement
• Quarterly bonuses and flexible working hours
• Conferences and an individual development budget
• Private healthcare and Multisport card