Scopic

Talent Community- MLOps Engineer

Rol remoto de MLOps con fit claro de ubicación del candidato.

Publicado19 jul 2026

Países elegibles1 país aceptado

Señal de seniorityMiddle

Modelo de trabajoRemoto

Ubicaciones aceptadas para candidatos

Estados Unidos

Resumen del rol

Contenido del rol extraído en secciones para revisar más rápido.

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.

I consent that the data provided in this form, and the attached CV, will be used for Scopic's recruiting purposes and email communications.
I consent to Scopic conducting an identity verification process as part of the hiring process. I understand that my personal information may be collected and processed for the purpose of verifying my identity in compliance with applicable laws.

Roles similares