Company profile

Kneron Tech Stack

Edge AI chips and software for on-device vision and audio models

Computer Hardware San Diego, California 51–200 employees Privately Held

Kneron designs integrated hardware and software for edge AI, building NPUs and the model toolchain that runs on them. Its stack pairs training frameworks (PyTorch, TensorFlow, ONNX) with low-level CUDA, OpenCL, DSP and QNX work, plus MLOps tooling like Kubeflow and MLflow. That points to a team compressing models onto its own accelerator while formalizing CI/CD for ML. Hiring is minimal and entirely engineering-focused.

Tech Stack 31 technologies

Core StackPython TensorFlow PyTorch AWS Docker Kubernetes MongoDB Flask JavaScript Django Kubeflow MLflow SageMaker C++ GitLab RAG Keras MXNet GCP Spark SQL SQLite OpenCV Caffe CUDA OpenCL ROS DSP QNX ONNX

What Kneron Is BuildingChallenges and projects from their job posts

◆Challenges

Optimizing deep learning models for edge hardware
Productionizing ML prototypes
Improving model accuracy
Scaling training workloads

▲Active Projects

Deploying deep learning models onto Kneron AI accelerator
Computer vision apps for 3D estimation, segmentation
Speech recognition and voice wakeup applications
CI/CD pipelines for machine learning
ML model performance monitoring tools
SLAM prototyping and vehicle testing

Hiring Activity

Minimal8 roles · 0 in 30d

Department

Engineering

Seniority

Mid

Senior

Intern

Junior

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About Kneron

Kneron is a privately held San Diego company founded in 2015 that develops edge AI solutions combining custom neural processing hardware with supporting software. It has delivered customized deployments for home appliances, surveillance systems and smartphones for international customers and partners. The company employs 51–200 people. Current engineering work spans computer vision, speech and voice applications, and SLAM prototyping with vehicle testing, with cloud infrastructure on AWS and GCP.

HeadquartersSan Diego, California

Company Size51–200 employees

Hiring MarketsUnited States

Frequently Asked Questions

What tech stack does Kneron use?

Kneron uses Python, C++, PyTorch, TensorFlow, Keras, ONNX, CUDA, OpenCL, OpenCV, ROS and QNX, with Docker, Kubernetes, Kubeflow, MLflow and SageMaker on AWS and GCP.

What is Kneron working on?

Kneron is deploying deep learning models onto its own AI accelerator, building computer vision and speech applications, developing ML monitoring and CI/CD tooling, and prototyping SLAM with vehicle testing.

Where is Kneron headquartered?

Kneron is headquartered in San Diego, California, and its current hiring is focused on engineering roles in the United States.

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How this profile is built

Kneron's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.