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Pipeline Controller Operator Jobs in California (NOW HIRING)

Sacramento County, CA

Water System Operator

Sacramento, CA · On-site

$81K - $98K/yr

... controlled valves, and associated equipment * The tools, materials, equipment and methods used in ... pipelines * Basic safety precautions and practices required when working in a variety of working ...

Roku

Software Engineer, Embedded Agentic AI

San Jose, CA · On-site

$170K - $210K/yr

As part of this team, you will help define how agentic AI systems are designed, built, and operated ... testing pipelines, controlled rollouts, drift detection, and mechanisms that prevent error ...

Valar Atomics

Senior OT Data Engineer

Torrance, CA · On-site

$110K - $150K/yr

The SCADA Engineer owns the FactoryTalk platform and operator-facing SCADA environment; you own cross-system data pipelines/models/storage/controlled egress. IC&E owns field instrumentation, PLC ...

Valar Atomics

Senior OT Data Engineer

Torrance, CA

$110K - $150K/yr

The SCADA Engineer owns the FactoryTalk platform and operator-facing SCADA environment; you own cross-system data pipelines/models/storage/controlled egress. IC&E owns field instrumentation, PLC ...

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Pipeline Controller Operator information

What is a pipeline controller operator?

Pipeline Controller Operators are professionals responsible for monitoring and managing the flow of oil, gas, or other materials through pipelines. They use advanced control systems and technology to ensure safe, efficient, and continuous pipeline operations. Their duties include detecting leaks, responding to emergencies, maintaining regulatory compliance, and coordinating with field personnel to address any issues. This role is critical for preventing environmental hazards and ensuring the reliable delivery of resources.

What skills and qualifications are needed to be a pipeline controller operator?

To thrive as a Pipeline Controller Operator, you need strong analytical skills, attention to detail, and typically a background in engineering, operations, or a related technical field. Familiarity with Supervisory Control and Data Acquisition (SCADA) systems, pipeline monitoring software, and relevant safety certifications such as API or DOT compliance is essential. Outstanding situational awareness, problem-solving abilities, and effective communication are important soft skills for this role. These competencies are crucial to ensure the safe, efficient, and uninterrupted operation of pipeline systems, preventing environmental hazards and maintaining regulatory compliance.

What is the difference between Pipeline Controller Operator vs Pipeline Technician?

AspectPipeline Controller OperatorPipeline Technician
CredentialsTypically requires a high school diploma, technical certifications, and safety trainingRequires similar certifications, often with additional technical or mechanical training
Work EnvironmentControl rooms, monitoring stations, and field sitesFieldwork, maintenance sites, and equipment inspection areas
Industry UsageUsed in oil, gas, and pipeline industries for monitoring and controlInvolved in installation, maintenance, and repair of pipelines

The Pipeline Controller Operator primarily monitors and controls pipeline operations from control centers, ensuring safety and efficiency. In contrast, the Pipeline Technician focuses on maintaining and repairing pipeline infrastructure in the field. Both roles require technical certifications and safety training, but their daily tasks and work environments differ significantly.

What are common challenges faced by pipeline controller operators and how can they be addressed?

Pipeline Controller Operators often face challenges such as monitoring large volumes of data simultaneously, responding quickly to abnormal operating conditions, and effectively communicating with field personnel during emergencies. Staying vigilant and maintaining strong attention to detail are crucial, as a small oversight can lead to significant safety or environmental incidents. Continuous training on updated control systems and emergency protocols, as well as fostering strong teamwork and communication skills, can help operators successfully manage these challenges.
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Pipeline Controller Operator jobs near you
Infographic showing various Pipeline Controller Operator job openings in California as of August 2026, with employment types broken down into 40% Full Time, 58% Part Time, 1% Contract, and 1% Nights. Highlights an 99% Physical, and 1% Remote job distribution.

Software Engineer - AI & Edge Kubernetes Orchestration

ZEDEDA

San Jose, CA • On-site

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

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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