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Manager Edge Computing Jobs in California (NOW HIRING)

Hadrian

Infrastructure Engineer

Los Angeles, CA · On-site

$115K - $151K/yr

... Support edge computing and IoT device deployments on factory floors • Drive build-vs-buy ... • Build and manage Kubernetes clusters (EKS in cloud, K0s/K3s at the edge) • Build CI/CD ...

Archer

Senior Software Engineer, Backend

San Jose, CA · On-site

$144K - $180K/yr

This role spans edge computing and cloud infrastructure, serving as a critical link between ... Experience building or managing applications on AWS * Proven problem-solving skills and the ability ...

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Manager Edge Computing information

What is the difference between Manager Edge Computing vs Network Engineer?

AspectManager Edge ComputingNetwork Engineer
CredentialsBachelor's in Computer Science or related, certifications like Cisco, cloud certificationsBachelor's in Computer Engineering, Cisco or CompTIA certifications
Work EnvironmentOversees edge computing projects, manages teams, collaborates with IT and operationsDesigns, implements, and maintains network infrastructure, often in data centers or enterprise settings
Industry UsageTechnology, manufacturing, IoT sectors focusing on edge solutionsTelecommunications, IT services, enterprise networks

The Manager Edge Computing focuses on leading edge computing initiatives, managing teams, and strategic planning. In contrast, a Network Engineer primarily designs and maintains network infrastructure. Both roles require technical certifications and work in related environments, but their responsibilities differ in scope and focus.

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Manager Edge Computing jobs near you
Software Engineer - AI & Edge Kubernetes Orchestration

Software Engineer - AI & Edge Kubernetes Orchestration

ZEDEDA

San Jose, CA • On-site

Full-time

Posted 6 days ago

Job description

Job Summary:
ZEDEDA unlocks the value of AI where it matters most, enabling enterprises to create, secure and operate edge AI at scale. The company is seeking a curious, self-driven entry level Software Engineer who will work alongside experienced engineers on real-world problems in edge orchestration, focusing on integrating AI tools and technologies into their daily workflow.
Responsibilities:
• Design, develop, and maintain software components that bridge AI model lifecycle management with Kubernetes-based edge orchestration.
• Build and extend Kubernetes controllers, operators, and Custom Resource Definitions (CRDs) to support AI workload scheduling and deployment at the edge.
• Work with ONNX, GenAI, and ML models — integrating them into production-ready pipelines and edge environments.
• Use AI coding agents (Claude Code, Copilot, Codex, etc.) as first-class tools in your daily development workflow.
• Participate in design discussions, write clean code, submit pull requests, and iterate rapidly based on feedback.
• Contribute to open-source components related to ZEDEDA's platform and the broader cloud-native ecosystem.
• Write and maintain Helm charts for deploying services into Kubernetes clusters.
• Collaborate with cross-functional teams across AI, infrastructure, and product to ship features end-to-end.
Qualifications:
Required:
• Bachelor's or Master's degree in Computer Science, AI/ML, or a related technical field — or equivalent practical experience.
• Foundational knowledge of machine learning concepts: neural networks, deep learning, model training and inference, and attention mechanisms (self-attention / transformers).
• Familiarity with ONNX models, GenAI model architectures, or frameworks like PyTorch or TensorFlow.
• Practical exposure to Kubernetes — understanding of pods, deployments, services, namespaces, and controllers. Familiarity with lightweight Kubernetes distributions such as k3s is a plus, particularly in the context of resource-constrained edge environments.
• Comfort working with Git, submitting pull requests, reading diffs, and collaborating in a version-controlled environment.
• Ability to work with vague or evolving problem statements and drive toward clarity independently.
• Language-agnostic development mindset — you pick the right tool for the job and learn what you don't know.
• Comfortable with basic Linux commands and shell scripting.
Preferred:
• Hands-on experience with Kubernetes advanced constructs: Custom Resource Definitions (CRDs), Operators, Controllers, and the kubeconfig API.
• CKA (Certified Kubernetes Administrator) or CKD certification, or active preparation for it.
• Experience with AI agent frameworks: LangChain, LangGraph, LangFuse, or similar.
• Demonstrated use of AI coding tools (Claude Code, GitHub Copilot, OpenAI Codex) in real development workflows — not just familiarity, but fluency.
• Prior contribution to, or porting of, open-source projects.
• Experience with CI/CD systems: Jenkins, CircleCI, GitHub Actions, or similar.
• Familiarity with AWS or Azure tooling.
• Knowledge of cloud-native technologies: Kafka, REST APIs, SSO/OAuth, microservices patterns.
• Exposure to Helm chart authoring, not just usage.
• Awareness of edge computing concepts, IoT, or distributed systems.
• Familiarity with edge AI hardware platforms and inference infrastructure: NVIDIA Jetson (Jetpack SDK), Qualcomm IQ9, NVIDIA Triton Inference Server, vLLM, or similar model serving frameworks.
• Familiarity with ArgoCD or other GitOps-based continuous delivery tools for Kubernetes.
Company:
ZEDEDA is a provider of distributed orchestration and virtualization software for Edge AI Compute. Founded in 2016, the company is headquartered in San Jose, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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