DevOps AI Engineer
Overview
You will own the AI/ML infrastructure and deployment pipelines for JC CORPORATIONS' AI applications. You will design, build, and automate scalable systems that deliver models to production. Your stack spans AWS, Azure, Google Cloud, Kubernetes, and MLOps tools. You will collaborate with data scientists and software engineers to streamline model deployment. This role combines deep DevOps expertise with AI/ML platform engineering, driving the backbone of our AI services.
What You'll Do8
- 1Design and implement CI/CD pipelines for AI/ML applications and services.
- 2Deploy and manage AI/ML workloads across AWS, Azure, or Google Cloud.
- 3Build and maintain MLOps infrastructure to automate model training, deployment, and monitoring.
- 4Automate containerized deployments with Docker and Kubernetes.
- 5Monitor and optimize infrastructure performance and cost.
- 6Implement security best practices in the deployment pipeline.
- 7Collaborate with data scientists to productionize machine learning models.
- 8Drive incident response and ensure high availability of AI services.
Requirements9
- 15+ years in DevOps, SRE, or platform engineering.
- 23+ years with Kubernetes and Docker.
- 3Strong cloud experience with AWS, Azure, or GCP.
- 4Proven track record building CI/CD pipelines with Jenkins, GitLab CI, or GitHub Actions.
- 5Experience with MLOps frameworks like MLflow, Kubeflow, or TFX.
- 6Proficiency in Python and shell scripting.
- 7Knowledge of infrastructure as code using Terraform or CloudFormation.
- 8Experience with monitoring tools such as Prometheus, Grafana, or Datadog.
- 9Familiarity with AI/ML model lifecycle and serving frameworks (e.g., TensorFlow Serving, SageMaker).
Salary Insight
$146 - $208k per year
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