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Edge Computing Jobs in California (NOW HIRING)

This role spans edge computing and cloud infrastructure, serving as a critical link between physical hardware and backend services. You may write software that runs on embedded devices one day and ...

Interns will join a fast-paced team environment, collaborating on software development, data pipelines, and deployment efforts across both cloud and edge computing environments. As a lean, early ...

The Market Development Manager will drive strategic growth and business development initiatives within Intel's Federal and Aerospace Division in the Edge Computing Group, focusing on identifying and ...

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Edge Computing information

See California salary details

$12

$25

$38

How much do edge computing jobs pay per hour?

As of Jun 9, 2026, the average hourly pay for edge computing in California is $25.22, according to ZipRecruiter salary data. Most workers in this role earn between $19.47 and $29.66 per hour, depending on experience, location, and employer.

Does edge computing have a future?

Edge computing is a growing field with increasing adoption across industries such as manufacturing, healthcare, and IoT, creating demand for professionals skilled in network architecture, security, and cloud integration. As data volume and latency requirements grow, the need for edge computing expertise is expected to expand, making it a promising career path for those with relevant technical skills and certifications. Job roles often involve working with distributed systems, real-time data processing, and hardware integration.

What are the key skills and qualifications needed to thrive in the Edge Computing position, and why are they important?

To excel in Edge Computing, you need a solid background in distributed systems, network engineering, and real-time data processing, typically supported by a degree in computer science, engineering, or a related field. Familiarity with tools and platforms such as Docker, Kubernetes, IoT frameworks, and edge-specific cloud solutions, along with relevant certifications like CompTIA IoT+ or Cisco certifications, is highly advantageous. Strong problem-solving skills, adaptability, and effective communication are crucial soft skills for collaborating across technical and business teams. These skills ensure effective design, deployment, and maintenance of decentralized computing solutions that drive innovation and performance in various industries.

What is an Edge Computing job?

An Edge Computing job involves designing, deploying, and managing computing resources closer to the data source to reduce latency and improve real-time data processing. Professionals in this field work with distributed computing, networking, and security to ensure efficient and reliable performance of edge devices. Roles often include Edge Engineer, Edge Architect, or IoT Specialist, requiring expertise in cloud-native technologies, AI, and edge infrastructure. These jobs are critical in industries like healthcare, manufacturing, and autonomous systems where low-latency decision-making is essential.

What are typical daily responsibilities of an Edge Computing professional?

As an Edge Computing professional, your daily tasks often include designing and deploying edge infrastructure, optimizing real-time data processing pipelines, and monitoring system performance to ensure low latency operations. You may coordinate with software developers, hardware engineers, and security specialists to integrate edge devices with cloud services. Troubleshooting network and latency issues, updating firmware, and implementing security protocols are also regular parts of the role. This multidisciplinary environment allows you to see immediate impacts from your work while constantly collaborating with cross-functional teams to solve complex problems.

What are the most commonly searched types of Edge Computing jobs in California? The most popular types of Edge Computing jobs in California are:
Infographic showing various Edge Computing job openings in California as of June 2026, with employment types broken down into 71% Full Time, 15% Part Time, 2% Temporary, 10% Contract, and 2% Nights. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution, with an average salary of $52,458 per year, or $25.2 per hour.
Software Engineer - AI & Edge Kubernetes Orchestration - San Jose, CA

Software Engineer - AI & Edge Kubernetes Orchestration - San Jose, CA

ZEDEDA

San Jose, CA • On-site

Full-time

Posted 5 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. They are seeking a curious, self-driven entry level Software Engineer to work on real-world problems in edge orchestration, collaborating with experienced engineers and contributing to the development of software components that bridge AI model lifecycle management with Kubernetes-based edge orchestration.
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.