Position Details
Job Title : Senior DevOps Engineer
Location Options : Greenwood Village, CO
Employment Type : CH
Visa : USC / GC
About the Role
Our Client is seeking a DevOps Engineer to join our ML Ops team . This position plays a key role in building scalable, secure, and efficient machine learning infrastructure across the organization.
You’ll work closely with data scientists and ML engineers to design, deploy, and maintain ML models in production—leveraging AWS, Kubernetes, Terraform, and CI / CD best practices to streamline workflows and accelerate ML initiatives.
Key Responsibilities
- Design, build, and maintain CI / CD pipelines for ML models and supporting infrastructure.
- Manage and optimize Kubernetes clusters for containerized ML workloads.
- Implement Infrastructure-as-Code (IaC) using Terraform for AWS cloud provisioning.
- Collaborate with ML engineers and platform teams for reliable deployments and monitoring .
- Automate provisioning, configuration, and deployments to ensure repeatability and scalability .
- Monitor systems using Prometheus, Grafana, CloudWatch , and other observability tools.
- Ensure security, compliance, and cost optimization across ML Ops environments.
- Contribute to internal tooling that enables faster and more efficient ML workflows.
Required Qualifications
Bachelor’s degree in Computer Science, Engineering , or related field (or equivalent experience).years of hands-on experience in DevOps, SRE, or Cloud Engineering .Strong proficiency in Kubernetes (EKS preferred) and Terraform .Experience with CI / CD tools – Jenkins, GitLab CI, CircleCI, or ArgoCD.Deep understanding of AWS services (EC, S, IAM, Lambda, VPC, etc.).Proficiency in Python, Bash, or similar scripting languages .Familiarity with monitoring / alerting tools such as Prometheus, Grafana, or CloudWatch.Experience supporting ML or data science teams is a strong plus.Excellent communication and problem-solving skills.Preferred Qualifications
Experience with ML platforms (MLflow, SageMaker, Kubeflow).Knowledge of GitOps tools like ArgoCD or Flux.Familiarity with Docker or other container build tools.Experience in regulated environments (security / compliance focus).AWS Certifications (, DevOps Engineer, Solutions Architect).Why Join Us
Work on high-impact projects at the intersection of AI / ML and infrastructure .Join a fast-growing, innovative ML Ops team .Gain access to cutting-edge cloud and ML technologies .Enjoy competitive pay, great benefits , and career development opportunities .