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.
responsibilities :
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.
