DevOps/MLOps Engineer - Remote (Greece)

About the job About us At Programize, we partner with teams of all sizes - from startups to established enterprises - across industries and continents to create innovative, high-impact software products. We don’t just implement requirements; we turn ambitious ideas into marketable software solutions we are genuinely proud to put our names on. With 200+ successfully delivered projects behind us, we’ve tackled everything from greenfield architectures to complex, large-scale platforms. Our vision is to become the go-to company for entrepreneurs and engineers, who want to design and develop impactful, scalable software systems. To achieve that, we need talented professionals to join our team, to share the thrill for technology and innovation. The Role Our team is collaborating with a company that aims to pioneer the future of play at one of the world's largest, most beloved toy companies and communities and we are looking for an experienced DevOps / MLOps Engineer who will own and lead DevOps across the department, supporting both the model training and inference infrastructure as well as the customer-facing applications. You will play a critical role in architecting, scaling, and maintaining the infrastructure that powers frontier models, and design systems that enable seamless training, evaluation, and deployment of cutting-edge AI models - ensuring reliability, performance, and safety at every stage of the lifecycle. You will also manage and scale the production environments that support customer-facing applications, internal services, and AI systems, ensuring consistency, reliability, and operational excellence across all platforms. What You Will Do Architect, manage and build cloud-based infrastructure (AWS, GCP, or Azure) optimized for large-scale distributed training as well as inference in scale. Architect, manage and build cloud-based infrastructure for the backend of our consumer based applications. Develop and maintain ModelOps pipelines for continuous training, testing, and deployment of frontier models. Design, build, and maintain CI/CD pipelines for large-scale AI and model development. Implement monitoring, observability, and rollback systems for AI services in production. Collaborate closely with ML engineers and researchers to streamline experimentation and model delivery. Develop infrastructure automation using tools such as Terraform, Kubernetes, and Docker. Establish best practices for reliability, security, and AI safety compliance within the model lifecycle. What You Have 5+ years of experience in DevOps, MLOps, or infrastructure engineering for ML systems. Proven experience managing large-scale training and inference pipelines in production. Deep expertise in Docker, Kubernetes, and cloud platforms (AWS, GCP, or Azure). Strong background with Infrastructure as Code tools (Terraform, etc.). Proficiency in Python and scripting (Bash or similar). Experience with CI/CD systems (GitHub Actions, GitLab CI, Jenkins, etc.). Familiarity with ML lifecycle tools such as MLflow, Kubeflow, Airflow. Familiarity with cloud-specific ML tools such as Sagemaker or Vertex.AI. Excellent problem-solving and debugging skills across complex distributed systems. Familiarity with monitoring and observability stacks (Prometheus, Grafana, etc.). Nice to Have B.Sc. or above in Computer Science, Software Engineering, or a related field. Strong understanding of data management, artifact storage, and model governance. Previous experience in early-stage teams or founding technical roles. What to expect from us Programize is built on respect, appreciation, and trust - toward both our customers and the people we work with every day. We believe in equal opportunity, diversity, flexibility, and continuous improvement, and we care deeply about creating an environment where people feel supported, motivated, and able to do their best work. So, in Programize you will find the following: A friendly, inclusive, and respectful working environment Competitive compensation and benefits Flexible work options, including on-site and fully remote work A collaborative, hands-on environment where ideas are encouraged Continuous learning and professional growth opportunities An international and diverse team A strong focus on work-life balance Private health insurance, including coverage for dependents