K
Kneron Tech Stack
Edge AI hardware and software platform for real-time inference
Kneron designs integrated edge AI solutions—hardware accelerators paired with optimized deep learning software—deployed in home appliances, surveillance, and mobile devices. The tech stack spans the full ML pipeline (TensorFlow, PyTorch, Keras for training; CUDA, OpenCL, ONNX for inference optimization) with production infrastructure (Kubernetes, MLflow, SageMaker), but hiring is purely engineering-focused with no sales, product, or operations roles in the last 30 days, suggesting either a mature go-to-market or a transition away from sales-driven growth.
Tech Stack 33 technologies
Core StackPython TensorFlow PyTorch AWS Docker Kubernetes MongoDB Flask JavaScript Django Kubeflow MLflow SageMaker C++ GitLab Keras MXNet GCP Spark SQL SQLite OpenCV Caffe CUDA OpenCL C/C++ ROS DSP QNX Android ONNX+1 more
What Kneron Is Building
◆Challenges
- Improving model accuracy
- Optimizing algorithm performance
- Productionizing ml prototypes
- Implementing ci/cd for ml
- Monitoring ml model performance
- Deep learning performance optimization
- Training workload scaling
- Optimizing models for edge hardware
▲Active Projects
- Real world deep learning solutions deployment
- Slam prototyping and vehicle testing
- Stoa deep neural network optimization
- End-to-end data collection and annotation
- Production lifecycle acceleration tools
- Model performance monitoring tools
- Ci/cd pipeline development
- Deploy deep learning models onto kneron ai accelerator
- Research and develop audio applications (speech recognition, voice recognition, voice wakeup)
- Research and develop computer vision applications (3d estimation, segmentation)
Hiring Activity
9 roles · 9 in 30d
Department
Seniority
Company intelligence
