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Edge Computing Jobs in California (NOW HIRING)

CTC USA, LLC

Computer Vision Engineer

Mountain View, CA · On-site

$130K - $154K/yr

Develop and integrate AI software on embedded and edge computing platforms for in-vehicle applications. * Design real-time perception systems operating under vehicle constraints including compute ...

Sapsol Technologies Inc

Golang Developer

Brea, CA · On-site

Relevant experience of 10+ Years • Design and implement edge computing solutions using AWS Greengrass v2. • Integrate AWS IoT Core for secure device connectivity, telemetry ingestion, and rule ...

HiveWatch

Senior IT Systems Engineer

El Segundo, CA · On-site

$111K - $152K/yr

Kotlin, Rust, TypeScript, Python • Expertise in AWS architecture and services • Experience in physical security, IoT, or edge computing environments • Expertise with advanced AWS services ...

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How much do edge computing jobs pay per hour?

As of Jul 18, 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.

Which 3 jobs will survive AI?

Edge computing jobs such as network engineers, cybersecurity specialists, and systems architects are likely to persist as they require complex problem-solving, infrastructure management, and security expertise that are difficult for AI to fully automate. These roles involve designing, maintaining, and securing distributed systems, often requiring certifications and hands-on experience. Skills in cloud platforms, programming, and real-time data analysis will remain valuable in this field.

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 processing needs expand and latency requirements grow, job opportunities in this area are expected to increase steadily in the coming years.

Does Tesla use edge computing?

Tesla employs edge computing in its vehicles to process data locally for features like Autopilot and real-time diagnostics, reducing reliance on cloud servers. This approach enhances response times and system reliability, which are critical for autonomous driving and vehicle safety systems.

What is the highest paying computing job?

In the field of edge computing, senior roles such as solutions architect, cloud engineer, or systems architect tend to have the highest salaries, often exceeding six figures annually. These positions typically require advanced skills in distributed systems, networking, and cloud platforms, along with relevant certifications like AWS or Cisco. Salary levels depend on experience, location, and company size.

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:
What are popular job titles related to Edge Computing jobs in California? For Edge Computing jobs in California, the most frequently searched job titles are:
What job categories do people searching Edge Computing jobs in California look for? The top searched job categories for Edge Computing jobs in California are:
Edge Computing jobs near you

Computer Vision Engineer

CTC USA, LLC

Mountain View, CA • On-site

$130K - $154K/yr

Other

Posted 9 days ago

Job description

Job Title:  Computer Vision Engineer – Advanced Development & Planning

Location:  Mountain View, CA

 

Duration: Long Term

About CTC:

Founded in 1996, CTC is a global IT services, Consulting and Business Solutions partner dedicated to helping organizations innovate, optimize, and grow. With over 2,000 professionals worldwide, we support more than 100 clients in transforming complex challenges into lasting competitive advantages.

 
Job Description:
Position Summary
Develop proof-of-concept (POC) computer vision systems for intelligent mobility and in-vehicle applications. The role focuses on rapidly evaluating, implementing, and deploying state-of-the-art computer vision and AI technologies on vehicle-grade edge computing platforms, bridging cutting-edge research and real-world intelligent mobility systems.
Responsibilities
  • Develop proof-of-concept systems using state-of-the-art AI and computer vision technologies.
  • Design and implement computer vision algorithms for object detection, tracking, semantic/instance segmentation, 3D scene understanding, visual localization, mapping, driver and occupant monitoring, and behavior recognition.
  • Build solutions using modern AI approaches including Vision Transformers (ViT), Vision-Language Models (VLMs), Multimodal AI, Foundation Models, Self-Supervised Learning, and Generative AI.
  • Evaluate and adapt the latest research papers and open-source models to automotive and intelligent mobility applications.
  • Integrate camera, vehicle, and sensor data to create innovative AI-driven applications.
  • Develop and integrate AI software on embedded and edge computing platforms for in-vehicle applications.
  • Design real-time perception systems operating under vehicle constraints including compute, memory, latency, power consumption, and robustness.
  • Optimize AI models for deployment on automotive SoCs, GPUs, and AI accelerators.
  • Prototype and evaluate end-to-end systems on vehicle platforms, embedded devices, and research vehicles.
  • Develop software for deployment and demonstration in vehicle-based proof-of-concept platforms.
  • Evaluate tradeoffs among accuracy, latency, memory footprint, and operational robustness.
  • Collaborate with researchers, software engineers, and system engineers to realize innovative concepts and demonstrations.
  • Stay up to date with emerging trends in computer vision, multimodal AI, edge AI, and intelligent mobility systems.
Qualifications
Required Qualifications
  • Master''s degree or higher in Computer Science, Electrical Engineering, Robotics, Artificial Intelligence, or a related field.
  • Strong background in Computer Vision and Machine Learning.
  • Hands-on experience with PyTorch, TensorFlow, OpenCV, or similar frameworks.
  • Experience implementing and training deep learning models including CNNs, Transformers, Vision Transformers (ViT), Vision-Language Models (VLMs), and multimodal architectures.
  • Strong programming skills in Python and C++.
  • Experience reading, reproducing, and extending recent AI/CV research publications.
  • Familiarity with Linux development environments.
  • Excellent verbal and written communication skills.
     
    Preferred Qualifications
  • Experience with Foundation Models, Large Vision Models, and Multimodal AI systems.
  • Experience with CLIP, SAM (Segment Anything), DINOv2, BEV-based perception models, or similar state-of-the-art vision technologies.
  • Experience with Generative AI and synthetic data generation.
  • Experience developing software on embedded Linux systems.
  • Experience with CUDA, TensorRT, ONNX Runtime, OpenVINO, or comparable inference optimization frameworks.
  • Experience optimizing and deploying AI models on edge devices and automotive computing platforms.
  • Experience with NVIDIA Jetson, NVIDIA DRIVE, Qualcomm Snapdragon Ride, or similar embedded AI platforms.
  • Experience with ROS/ROS2, sensor fusion, or robotic/automotive systems.
  • Experience in automotive, robotics, autonomous systems, or intelligent transportation systems.
  • Publications in leading AI, robotics, or computer vision conferences are a plus.

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