This is a remote position.
Join Our Talent Community for MLOps EngineersAt Scopic, we’re always planning ahead—looking for innovative MLOps professionals who are passionate about bridging machine learning and scalable production systems. Join our Talent Community tailored for MLOps Engineers, and gain more than just a chance to apply for a job—you’ll become part of a proactive initiative connecting you with future roles at the intersection of AI, automation, and infrastructure.
Joining our MLOps Talent Community isn’t about filling an immediate vacancy—it’s about preparing for the next wave of opportunities that match your skills, experience, and vision for the future of AI operations.
Priority Access to Opportunities: Gain early and exclusive access to upcoming roles that fit your technical expertise in. This priority access increases your chances of finding the right job at the right time without competing with the general market.
Ongoing Engagement: Stay informed with regular updates about new projects and potential roles. Our engagement initiatives are designed to keep you connected with our company culture and developments, ensuring you’re always prepared for the next opportunity.
Expanded Opportunities: Enjoy quicker placement processes and less hiring friction. As a community member, you won’t be rushed through assessments and interviews. Instead, you'll have the time you need to showcase your skills properly, enhancing your experience with us and ensuring a fit that’s right for everyone.
Have 3+ years of hands-on experience in MLOps—from model deployment to monitoring and automation.
Are proficient with Docker, Kubernetes, and infrastructure-as-code tools such as Terraform.
Have experience with CI/CD for ML, using tools like Jenkins, GitLab CI/CD, or similar.
Know how to operationalize machine learning using platforms such as MLflow, Kubeflow, SageMaker, or Vertex AI.
Have strong Python programming skills and familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
Understand cloud-based AI workflows and have hands-on experience with AWS, GCP, or Azure.
Are passionate about scalable ML pipelines, AI model reliability, and continuous improvement.
You want to stay connected to AI-driven projects and future-ready MLOps roles.
You thrive in automation, optimization, and data-driven infrastructure environments.
You appreciate a forward-thinking approach to recruitment—one that values your long-term growth and expertise.
Joining our Talent Community for MLOps Engineers means initiating a dialogue about your future with us. We’re eager to learn more about you and to explore how your skills and ambitions can align with our evolving needs.
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