Consultant Nicole Lee
Job Ref 1146920/001
Date posted 29 June 2022taipei tech-transformation/development-programming 2022-06-29 2022-08-28 it Taipei TW Robert Walters https://www.robertwalters.com.tw https://www.robertwalters.com.tw/content/dam/robert-walters/global/images/logos/web-logos/square-logo.png
Our client is looking for an AI Engineer in Taipei.
- Experience with implementing machine learning algorithms or computer vision in practice
- Write clean and maintainable code with unit tests and design documents
- Accelerating and optimizing DL algorithms on various platforms
- Experience with convolutional neural networks and their pruning and quantization
- Experience with compressed representation of neural networks and frameworks for conveying their architectures to an edge device
- Working on areas such as inter-process data sharing, component abstraction layers and communication, and process scheduling
- Skilled in breaking down problems, estimating efforts and documenting problem statements
- Mentor junior engineers, document design decisions and perform code reviews
- Collaborate with the Data Science team and Development team to build state-of-the-art models, test and validate new algorithms and integrate the algorithms with the existing frontend and backend systems
- Review and finalize deliverables to ensure high quality content consistent with client and company expectations
- BS in Computer Science, Electrical Engineering or similar field
- Experience with one modern language such as Java, C++, Python including object-oriented design. Strong experience in C/C++ programing is a plus
- Experience with machine learning tools and deep learning algorithms and techniques, including but not limited to:
- PyTorch, TensorFlow, Keras
- OpenCV, Scikit-learn, pandas, numpy
- Experience with EdgeAI, TinyML and other production level implementation frameworks, including at least one of the following:
- TensorFlow Lite (TFLite)
- NVIDIA Jetson™
- Paddle-mobile, Paddle-Lite
- Experience with model compression techniques including QAT, model distillation, pruning, quantization, model binarization, and others for deep learning models
- Experience with implementing novel deep neural network architectures and developing advanced training algorithms to support model structure training, auto pruning and low-bit quantization
- Able to work independently on problems and in highly collaborative team environments
- Ph.D. or Master’s degree in a scientific or engineering domain
- Experience with contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
- Experience with parallel computing, GPU/CUDA, DSP, and OpenCL programming is a plus
- Experience with MLOps and other production level implementation frameworks and pipelines
- Top-tier conference publication records, including but not limited to CVPR, ICCV, ECCV, NIPS, ICML, are strong plus
- Fluency with machine learning algorithms, such as CNN, RNN, reinforcement learning, support vector machines, and graph-based models
- Experience with messaging systems, Docker, Kubernetes, Spark, EMR, and cloud platforms (AWS or Azure)
- Team management and mentoring junior members
- Experience with version control systems (e.g. Git flow)
- Strong oral and verbal communication skills
- Experience working with international cross-functional teams and/or customer facing work
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