DevOps/MLOps Engineer

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Scopic

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2006

Software Development • AI • Digital Marketing

Scopic is a software development company specializing in custom software solutions, mobile and web development, AI consulting, and digital marketing services. With expertise in various technologies such as PHP, Node. js, and AWS, Scopic caters to diverse industries including healthcare, finance, and education. They focus on transforming client ideas into innovative applications while ensuring high-quality user experiences and effective marketing strategies.

📋 Description

• Design and implement CI/CD pipelines for both general applications and machine learning workflows • Build and maintain scalable infrastructure using containerization (Docker, Kubernetes) and infrastructure-as-code tools • Manage and optimize cloud-based environments across AWS, GCP, or Azure • Deploy, monitor, and maintain machine learning models and pipelines in production environments • Establish and improve monitoring, logging, and alerting systems for application and ML infrastructure health • Automate deployment, scaling, and operational tasks to reduce manual overhead and improve reliability • Collaborate with software engineers and data scientists to understand deployment requirements and optimize system architecture • Ensure security, performance, and reliability across infrastructure and application layers • Troubleshoot and resolve infrastructure, deployment, and operational issues • Maintain documentation and best practices for infrastructure and deployment processes

🎯 Requirements

• 3+ years of hands-on DevOps or infrastructure engineering experience • Strong proficiency with containerization and orchestration (Docker, Kubernetes) • Experience with infrastructure-as-code tools such as Terraform, CloudFormation, or Ansible • Solid understanding of CI/CD concepts and hands-on experience with tools like Jenkins, GitLab CI/CD, GitHub Actions, or similar • Strong programming skills in Python, Bash, or Go for automation and scripting • Hands-on experience with at least one major cloud platform (AWS, GCP, or Azure) • Familiarity with monitoring and logging tools (Prometheus, ELK stack, CloudWatch, or similar) • Experience with ML operationalization and deployment platforms such as MLflow, Kubeflow, SageMaker, or Vertex AI is a plus • Understanding of ML frameworks and workflows (TensorFlow, PyTorch, scikit-learn) is a plus • Strong problem-solving skills and ability to work independently on infrastructure challenges

🏖️ Benefits

• Paid training and other professional opportunities • Flexibility and freedom to work from anywhere with a stable internet connection • Consistent flow of engaging, challenging work to do • Annual pay increases for good performance