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4-6 years
6-10 years
10-15 years
More than 15 years
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Offline
Machine Learning Software Engineer @AMD2021 ~ Present
・
Machine Learning Engineer
Within two months
deep learning. Deep Learning Engineer , CVITEK, OctSep 2021 Spin off from Bitmain . Mainly focus on deep learning accelerator (so called NPU or TPU) and stereo vision accelerator. Deep learning accelerator a. Research and prototype the int8, int4 and bf16 quantization algorithm. b. Mix-precision algorithm based on Post training, result had applied patent in US and CN (USA1, CNA). c. Model compression flow (heterogeneous quantization). d. Design quantization flow in deep learning compiler (graph optimization, calibration, fine tuning, mix-precision). e. Implement frontend of deep learning compiler (high
Employed
Full-time / Interested in working remotely
6-10 years
National Chiao Tung University
・
Computer Science
AI Engineer @Revlis Biotech Co. Ltd., Yunlin County, Taiwan2022 ~ Present
・
AI工程師、機器學習工程師、深度學習工程師、資料科學家、Machine Learning Engineer、Deep Learning Engineer、Data Scientist
Within two months
Gavin Jang AI Engineer Taichung City, Taiwan Highly skilled in Machine/ Deep Learning, Statistics, Time Series Analysis, and Multivariate Analysis. Have built a WaveGAN model for generating 12 LEADs ECG signals and a U-Net model for reconstructing 12 LEADs ECG signals. Accomplishments De-Noising Auto-Encoder for ECG Signals U-Net for Reconstructing 12 LEADs ECG Signals WaveGAN for Generating 12 LEADs ECG Signals Deep Learning Model for Heart Disease Diagnosis AI-Based Blood Sugar Detection with ECG Signals Data Visualization and Deep Learning Model for Deep-Sea Fishery Work History AI Engineer Revlis Biotech Co
Employed
Full-time / Interested in working remotely
10-15 years
National Sun Yat-sen University
・
Biological Oceanography, Multivariate Analysis, Time Series Analysis 
Teaching Assistant @Georgia Institute of Technology | The University of British Columbia2014 ~ 2019
・
PHD Student
More than one year
Lindsay Yuling Chuang I am a Ph.D. candidate of Geophysics at Georgia Tech. My research mainly focus on using various machine learning and deep learning algorithms to solve different seismological problems. I am a data enthusiastic with 10+ years full stack developing experiences. Atlanta, GA, USA Publication Journal paper Earthquake transformer - an attentive deep-learning model for simultaneous earthquake detection and phase picking publication dat SM Mousavi, WL Ellsworth, W Zhu, LY Chuang, GC Beroza Nature communications, 1-12 Plateau subduction, intraslab seismicity, and the Denali (Alaska) volcanic gap publication date L Chuang
Intern / Interested in working remotely
6-10 years
The University of British Columbia
・
M.S. in Geophysics
機器學習演算法工程師
More than one year
吳杰 我畢業於交通大學電子工程研究所，目前專注於機器學習這塊領域。碩士論文主要是研究：如何在物聯網中，利用機器學習的演算法降低總能量消耗。 自己在服役期間，用Deep learning做了一些side project，例如：輸入照片，自動辨別性別與年齡，語意分析，走迷
Full-time / Interested in working remotely
4-6 years
交通大學
・
電子工程系
Principal Engineer @Coretronic Corporation, 中強光電2020 ~ 2022
・
Machine Learning Engineer
Within one month
Employed
Full-time / Interested in working remotely
6-10 years
國立台灣大學
・
經濟學Research and Development Engineer @Kyoto Robotics2020 ~ Present
・
Engineer
Within one year
Employed
Full-time / Interested in working remotely
6-10 years
IIT Bombay
・
MTech in Electronic SystemsEmployed
・
Ready to interview
Full-time / Interested in working remotely
6-10 years
國立臺灣科技大學
・
電機系
Senior Software Engineer @U-NEXT Co., Ltd.2021 ~ Present
・
Software Engineer
Within one month
Tensorflow/Keras/OpenCV Software Engineer • 盛星科技 | Astra Inc. 十二月四月Build innovative computer vision and pedestrian detection backend service - Build and maintain a high availability of deep learning-based computing systems - Develop human detection and facial recognition deep learning models and algorithms [Core technology] - Golang/Python - AWS/DynamoDB/SQS/EC2 - Tensorflow/Keras/OpenCV/openVINO Platform Engineer Intern • Intel 二月六月Survey internal paper and develop the internal script for Xeon SP testing platform - FPGA, OpenCL deep learning and machine learning research - Develop
Employed
Full-time / Interested in working remotely
4-6 years
Nation Taiwan University
・
Bioelectronic and Bioinformatics
Algorithm Engineer @Delta Electronics2017 ~ Present
・
Algorithm Engineer
Within one month
莊承翰 The devil is in the detail. Video and Image Algorithm, Deep learning, Software development [email protected] Summary Over 8 years of experience in deep learning and more than 10 years of experience in computer vision/image processing. Capable of independently or collaboratively building AI (image/video) products from scratch with various teams. Analyzing, and improving deep learning systems. Kaggle Top 1% ( 16 /Sartorius - Cell Instance Segmentation (2021/12~2021/12) Top 4% ( 85 /Human Protein Atlas Image Classification (2018/11~2019/1
Employed
Full-time / Not interested in working remotely
4-6 years
National Chin-Yi University of Technology
資料分析師 @天鏡科技
資料分析師
Within one year
categorical data, text data, imbalance data. Languages Mandarin, English Experience Data Analyst - skymirror co.，AprMaydata modelling Make statistical model for daily or long term trading strategy of Taiwan, China, US future market, and oversea financial derivatives. Reviewing and improving the model. Applying financial indicator or machine learning e.g. Xgboost and RNN to predict market. And improve the model. Study new technical about deep learning or mathematical algorithm and try it on trading. Main goal is to improve model accuracy. Data visualization Communicate with manager how to calculate and decide
Full-time / Interested in working remotely
6-10 years
國立台北大學
・
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Professional Background
Current status
Employed
Job Search Progress
Professions
Machine Learning Engineer
Fields of Employment
Semiconductor
Work experience
6-10 years
Management
Skills
Languages
Chinese
・
Native or Bilingual
English
・
Intermediate
Job search preferences
Positions
Machine Learning Engineer
Job types
Full-time
Locations
Taiwan, Taipei, 台灣
Remote
Interested in working remotely
Freelance
Educations
School
National Chiao Tung University
Major
Computer Science
Rocking Lai
Introduction
I am a deep learning engineer as well as professional software engineer.
I take part in various deep learning & computer vision projects, from software application to AI chip.
Also have the experience of developing video surveillance system (full-stack).
In addition, I strive for learning and constantly looking for ways to share my knowledge.
I am the mentor of Coursera, which helps students in learning computer vision and machine learning.
Skills
Domain Knowledge
- GPU Programming
- Deep Learning Compiler
- Neural Network Quantization
- Computer Vision Algorithm
- Surveillance System
Tool
- C++
- Python
- Pytorch
- OpenCV
Experience
Machine Learning Software Engineer, AMD, Sep 2021 - Present
- Develop GPU backend of various deep learning framework. Eg. PyTorch, Tensorflow, Onnx runtime
a. Implement and optimize GPU kernel
b. Proposed complex fused kernel, such as gemm + layernorm, gemm + reduction, gemm + softmax.
c. Low precision arithmetic for deep learning.
Deep Learning Engineer, CVITEK, Oct 2019 - Sep 2021
- Spin off from Bitmain.
- Mainly focus on deep learning accelerator (so called NPU or TPU) and stereo vision accelerator.
- Deep learning accelerator
a. Research and prototype the int8, int4 and bf16 quantization algorithm.
b. Mix-precision algorithm based on Post training, result had applied patent in US and CN (US20220129736A1, CN114492721A).
c. Model compression flow (heterogeneous quantization).
d. Design quantization flow in deep learning compiler (graph optimization, calibration, fine tuning, mix-precision).
e. Implement frontend of deep learning compiler (high level optimization and lowering to low level IR).
f. Inference simulator via high level IR.
g. Co-work with IC designer to design the cmodel of AI accelerator.
- Stereo Vision accelerator
a. Prototype the hardware-friendly stereo matching algorithm.
b. Co-work with IC designer to design the cmodel.
Deep Learning Engineer, Bitmain, Aug 2018 - Oct 2019
- Mainly focus on deep learning accelerator (so called NPU or TPU and so on)
- Research of deep learning algorithm for edge AI accelerator.
a. int8 and bf16 quantization algorithm.
b. Post training based mix-precision algorithm.
c. Quantization-aware training flow. - Deep learning compiler
a. Quantization tool (calibration, fine tuning).
b. Inference simulator for high level IR (cpu & gpu).
c. Co-work with IC designer to design the cmodel of AI accelerator.
Algorithm Engineer, ULSee, Jun 2017 ~ Aug 2018
- Vision algorithm for robot (object detection, gesture recognition, posture recognition).
- Facial landmark tracking algorithm.
- Improve face recognition flow.
- Driver fatigue detection, phone talking detection for ADAS (Advance driver assistance system).
- Plan & design the face recognition system for various projects. (IP camera integration, video
management, lead the scrum flow).
Software Engineer, NUUO, Sep 2014 ~ Oct 2017
- Design and maintained the Network video recorder (NVR). It is an embedded Linux, which can received video
stream from IP camera, various type of recording, video analytic, third party integration.
- Develop new features for NVR client, which can play live video, playback video, smart search video, event
management...etc.
- Develop SDK of NVR, provide a way for third party to integrate our NVR.
Volunteer
Course Mentor, Jan 2017 - Feb 2019
Machine Learning, offered by Stanford University.
Fundamentals of Digital Image and Video Processing, offered by Northwestern University.
Education
Master's degree, Computer Science and Information Engineering
National Chiao Tung University (2012 - 2014)
Bachelor's degree, Computer Science
National Chiao Tung University (2008 - 2012)
Publication
- Toward Community Sensing of Road Anomalies Using Monocular Vision, IEEE Sensors Journal (Volume:16 , Issue: 8 ) 2016
- Vision-Based Road Bump Detection Using a Front-Mounted Car Camcorder, IEEE International Conference on Pattern Recognition (ICPR 2014)
Patent
- Mixed-precision quantization method for neural network, US20220129736A1 (2021)
- 神經網路的混合精度量化方法, CN114492721A (2020)
Rocking Lai
Introduction
I am a deep learning engineer as well as professional software engineer.
I take part in various deep learning & computer vision projects, from software application to AI chip.
Also have the experience of developing video surveillance system (full-stack).
In addition, I strive for learning and constantly looking for ways to share my knowledge.
I am the mentor of Coursera, which helps students in learning computer vision and machine learning.
Skills
Domain Knowledge
- GPU Programming
- Deep Learning Compiler
- Neural Network Quantization
- Computer Vision Algorithm
- Surveillance System
Tool
- C++
- Python
- Pytorch
- OpenCV
Experience
Machine Learning Software Engineer, AMD, Sep 2021 - Present
- Develop GPU backend of various deep learning framework. Eg. PyTorch, Tensorflow, Onnx runtime
a. Implement and optimize GPU kernel
b. Proposed complex fused kernel, such as gemm + layernorm, gemm + reduction, gemm + softmax.
c. Low precision arithmetic for deep learning.
Deep Learning Engineer, CVITEK, Oct 2019 - Sep 2021
- Spin off from Bitmain.
- Mainly focus on deep learning accelerator (so called NPU or TPU) and stereo vision accelerator.
- Deep learning accelerator
a. Research and prototype the int8, int4 and bf16 quantization algorithm.
b. Mix-precision algorithm based on Post training, result had applied patent in US and CN (US20220129736A1, CN114492721A).
c. Model compression flow (heterogeneous quantization).
d. Design quantization flow in deep learning compiler (graph optimization, calibration, fine tuning, mix-precision).
e. Implement frontend of deep learning compiler (high level optimization and lowering to low level IR).
f. Inference simulator via high level IR.
g. Co-work with IC designer to design the cmodel of AI accelerator.
- Stereo Vision accelerator
a. Prototype the hardware-friendly stereo matching algorithm.
b. Co-work with IC designer to design the cmodel.
Deep Learning Engineer, Bitmain, Aug 2018 - Oct 2019
- Mainly focus on deep learning accelerator (so called NPU or TPU and so on)
- Research of deep learning algorithm for edge AI accelerator.
a. int8 and bf16 quantization algorithm.
b. Post training based mix-precision algorithm.
c. Quantization-aware training flow. - Deep learning compiler
a. Quantization tool (calibration, fine tuning).
b. Inference simulator for high level IR (cpu & gpu).
c. Co-work with IC designer to design the cmodel of AI accelerator.
Algorithm Engineer, ULSee, Jun 2017 ~ Aug 2018
- Vision algorithm for robot (object detection, gesture recognition, posture recognition).
- Facial landmark tracking algorithm.
- Improve face recognition flow.
- Driver fatigue detection, phone talking detection for ADAS (Advance driver assistance system).
- Plan & design the face recognition system for various projects. (IP camera integration, video
management, lead the scrum flow).
Software Engineer, NUUO, Sep 2014 ~ Oct 2017
- Design and maintained the Network video recorder (NVR). It is an embedded Linux, which can received video
stream from IP camera, various type of recording, video analytic, third party integration.
- Develop new features for NVR client, which can play live video, playback video, smart search video, event
management...etc.
- Develop SDK of NVR, provide a way for third party to integrate our NVR.
Volunteer
Course Mentor, Jan 2017 - Feb 2019
Machine Learning, offered by Stanford University.
Fundamentals of Digital Image and Video Processing, offered by Northwestern University.
Education
Master's degree, Computer Science and Information Engineering
National Chiao Tung University (2012 - 2014)
Bachelor's degree, Computer Science
National Chiao Tung University (2008 - 2012)
Publication
- Toward Community Sensing of Road Anomalies Using Monocular Vision, IEEE Sensors Journal (Volume:16 , Issue: 8 ) 2016
- Vision-Based Road Bump Detection Using a Front-Mounted Car Camcorder, IEEE International Conference on Pattern Recognition (ICPR 2014)
Patent
- Mixed-precision quantization method for neural network, US20220129736A1 (2021)
- 神經網路的混合精度量化方法, CN114492721A (2020)