ML / DevOps Engineer (m/f/d)

Nasze wymagania: 3+ years DevOps/SRE/MLOps experience with production systems. Strong Kubernetes: workloads (Deployments, StatefulSets, Jobs/CronJobs), networking (Ingress/Service), storage (PVC/CSI), autoscaling, prod diagnostics. Docker expertise (builds, optimization, hardening), Helm/Customize. GitLab CI/CD pipelines (environments, artifacts, rollouts/rollbacks). Python + ML libs (scikit-learn, PyTorch/TensorFlow) for model packaging. Observability: Prometheus/Grafana/ELK-Loki, alerts & incident analysis. Linux + automation (bash, IaC welcome). Fluent English and Polish (both written and spoken). Creative, open-minded, and proactive approach to problem-solving. Ability to work in a dynamic environment and build solutions from scratch. Mile widziane: GPU on K8s (labeling, affinities, monitoring). MLOps tools (MLflow, Kubeflow, Airflow). IaC (Terraform/Ansible). Regulated environments (pharma/finance). O projekcie: We are seeking a ML / DevOps Engineer to join our team to support the software development and biotechnology departments, addressing the evolving needs of both areas. You will work on internal projects within a biotechnology environment focused on AI, GPU cluster operations, and building the company’s global MLOps stack. This is a newly created role that combines maintaining and developing DevOps infrastructure with building MLOps capabilities from the ground up. In addition to daily responsibilities related to CI/CD pipelines, Kubernetes environments, and system reliability, you will play a key role in designing and implementing our future MLOps ecosystem. This position requires a hands-on, proactive mindset – we are looking for someone who enjoys working in less-defined environments, is comfortable with manual and evolving processes, and is motivated to create new solutions rather than follow fully established ones. Zakres obowiązków: Design, develop, and maintain end-to-end CI/CD pipelines in GitLab for ML apps/services (tests, quality gates, image building, artifact versioning, multi-env deployments). Containerize apps/services with Docker, prepare Helm/K8s manifests. Maintain Kubernetes clusters: stability, security, scalability, collaborate on changes and troubleshooting. Manage on-prem K8s clusters: upgrades, config, capacity planning, issue support. Implement observability (Prometheus, Grafana, ELK/Loki) for metrics, logs, alerts. Handle model/data versioning and artifacts with Data Science teams. Basic Python/ML integration for production models (API/batch). Ability to work in a dynamic environment and build solutions from scratch. Oferujemy: Daily cooperation and know-how exchange with experts. Additional benefits: a prepaid lunch card, private medical care, subsidized sports card, and office fruit provision. Internal Development initiatives, including soft & leadership skills training programs. Recognition Program. Employee Referral Program. Support & incentive bonus for completing Ph.D. Various sports and engagement initiatives.