3 months ago
San Jose, CA, USAEntry Level
Base Salary
$120k - $140k/yr
Responsibilities
- Design, develop, and maintain software connecting AI model lifecycle management with Kubernetes-based edge orchestration.
- Build and extend Kubernetes controllers, operators, and Custom Resource Definitions to support AI workload scheduling and deployment at the edge.
- Integrate ONNX, GenAI, and machine learning models into production-ready pipelines and edge environments.
- Use AI coding agents as first-class tools in daily development workflows.
- Participate in design discussions, write clean code, submit pull requests, and iterate 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 AI, infrastructure, and product teams to ship features end-to-end.
Requirements
- Recent graduate or candidate with up to two years of industry experience.
- Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related technical field, or equivalent practical experience.
- Foundational knowledge of neural networks, deep learning, model training and inference, and attention mechanisms including self-attention and transformers.
- Familiarity with ONNX models, GenAI model architectures, PyTorch, or TensorFlow.
- Practical exposure to Kubernetes concepts including pods, deployments, services, namespaces, and controllers.
- Comfort with Git, pull requests, diffs, version-controlled collaboration, basic Linux commands, and shell scripting.
- Ability to work through vague or evolving problems independently and learn new tools as needed.
- Preferred qualifications include experience with Kubernetes CRDs, Operators, Controllers, kubeconfig API, Helm chart authoring, AI agent frameworks, AI coding tools, open-source projects, CI/CD systems, AWS or Azure, Kafka, SSO/OAuth, microservices, edge computing, IoT, distributed systems, edge AI hardware, model-serving frameworks, and GitOps tools.
- Preferred certifications include CKA or CKD, or active preparation for them.
Benefits
- Base pay range of $120,000-$140,000.
- Performance-based bonuses and comprehensive medical benefits.
- Hybrid work flexibility; the position is based in San Jose and requires three days onsite.
- Relocation assistance and travel or commuting expenses are not provided.
- Access to AI productivity tools, on-the-job learning, and opportunities for technical growth and advancement.
Tech Stack
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