Algorithm Engineer (Deep Learning)
Job description
- You will be responsible for research, development and deployment of real world deep learning solutions while building Computer Vision, Speech, Machine Learning, and Robotics
- Driveend to end data collection/annotation, model training and model evaluation
- Optimizing and accelerating deep learning algorithms on various Kneron platforms (SOC, edge, server etc) and accelerators (DSP, NPU etc).
- Improving model accuracy by understanding failures, finding redundancies in data and staying on top of the latest in model architectures and training algorithms.
- Contributing to the backend or edge infrastructure to scale model training and inference workload including training pipelines, evaluation, and model deployment
Requirements
- MS or PhD in Computer Science/Engineering with 2+ years of professional experience or equivalent experience
- Strong background in at least one of area of machine learning, such asgenerative models (GANs, VAE, etc.), segmentation, object detection, human tracking
- Strong programming skills in Python and C/C++; strong software design skills
- Experience working with modern deep learning frameworks including OpenMMlab, Keras, Tensorflow, PyTorch, MXNet
- Experience with improving efficiency of AI algorithms for deployment
- Ability to multitask effectively in a dynamic environment
- Strong debugging, problem-solving and analytical skills
- Excellent interpersonal, written and oral communications skills
Preferred:
- Familiarity with building DL algorithms (neural architecture search, active learning, pruning, quantization etc) and working with data pipelines (ETL, data lake etc).
- Familiarity with scene understanding, learning 3D representations, synthetic data, temporal data in computer vision.
- Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open-source repositories (e.g., GitHub)
The ideal candidate will have a passion for generating new ideas, be a proactive and quick learner, and be able to demonstrate creativity and innovation.
Location
Contact
E-mail:career@kneron.us

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