Quick overview
Job description
What You'll Get To Do
- Build and maintain CI/CD pipelines across robotics, AI, and software systems using tools such as GitHub Actions.
- Design and manage cloud-native, containerized infrastructure using Kubernetes, Docker, and related technologies.
- Deploy and support workloads across cloud and edge environments.
- Improve developer workflows through automation, tooling, and infrastructure enhancements.
- Support testing, packaging, deployment, and observability for distributed robotics and AI systems.
- Collaborate cross-functionally with robotics, ML, and platform engineering teams to improve reliability and scalability.
- Optimize build systems, monorepos, and deployment workflows for complex engineering environments.
What You Have
- Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience.
- 3-7 years of experience in DevOps, Platform Engineering, Cloud Infrastructure, SRE, or related roles.
- Strong experience with Kubernetes, Docker, and cloud-native infrastructure.
- Experience building and maintaining CI/CD systems in complex engineering environments.
- Strong scripting or programming skills in Python, Bash, Go, or similar languages.
- Solid understanding of Linux systems, networking, and distributed systems fundamentals.
- Strong problem-solving skills and ability to work effectively across multidisciplinary teams.
The Extras That Set You Apart
- Experience supporting robotics, autonomous systems, IoT, or edge computing environments.
- Experience with MLOps, AI infrastructure, GPU workloads, or ML deployment pipelines.
- Familiarity with ROS, Terraform, Helm, ArgoCD, or related infrastructure tooling.
- Experience managing large monorepos, build systems, and developer platforms.
- Experience building observability and reliability systems for distributed infrastructure.
- Kubernetes certifications such as CKA, CKAD, or CKS.
- Bias for action and ability to thrive in fast-moving, ambiguous environments.
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