AI Cloud DevOps Lead for ML Pipelines

Bitdeer Technologies Group; Austin (TX); On-site; USD 150,000 - 210,000; Full time

Job summary

Bitdeer Technologies Group in Austin, TX, seeks a Cloud Senior DevOps Engineer to lead deployment and infrastructure operations for AI cloud products, ensuring speed, security, and reliability across pipelines and platforms.

You will drive automation, build cloud-native architectures with Kubernetes and Docker, implement MLOps workflows, and partner with R&D, Security, and Data Science to scale performance and resilience.

Qualifications

• Bachelor’s degree or higher in a technical field with hands-on DevOps/SRE/cloud experience.
• Strong Linux networking, modern cloud architectures, and container orchestration knowledge.
• Proficiency in Go, Python, or Shell for automation, tooling, and pipelines.

Responsibilities

• Design, implement, and maintain end-to-end CI/CD pipelines for software and ML models.
• Build, optimize, and scale cloud-native infrastructure using Kubernetes and Docker.
• Own high-availability design, DR strategies, capacity planning, and tuning.
• Lead IaC provisioning with Terraform, Ansible, and Helm across clouds.
• Develop observability with Prometheus, Grafana, and logs/metrics pipelines.
• Collaborate with R&D, Data Science, Security, and Biz teams to improve throughput.
• Enforce security practices, Zero Trust, secrets management, and compliance.
• Provide incident leadership, RCA, and preventative remediation.

Skills

Linux & Networking

Docker & Kubernetes

Cloud Platforms

Go / Python

CI/CD / MLOps

IaC

SRE Principles

Observability

Cross-team Collaboration

Education

Bachelor's degree in Computer Science / Engineering

Tools

Terraform

Ansible

Helm

Job description

Bitdeer Technologies Group in Austin, TX, seeks a Cloud Senior DevOps Engineer to lead deployment and infrastructure operations for AI cloud products, ensuring speed, security, and reliability across pipelines and platforms.

You will drive automation, build cloud-native architectures with Kubernetes and Docker, implement MLOps workflows, and partner with R&D, Security, and Data Science to scale performance and resilience.