Senior Machine Learning Scientist
Amazon, Australia
– Developing Large Language Models (LLM), recommender systems, and deep learning solutions.
– Contributing to scalable machine learning pipelines in global production environments.
Senior Research Lecturer
Deakin University, Australia
– Conducted research on neural reasoning, structured video representation, and medical computer vision.
– Delivered lectures and supervised graduate students in computer vision and deep learning projects.
Research Fellow
Deakin University, Australia
– Focused on structured video understanding and human behavior analysis for video analytics.
– Published in top-tier conferences and led grant-funded research initiatives.
Research Engineer – AWS Rekognition
Amazon, Greater Seattle Area
– Built large-scale computer vision pipelines for AWS Rekognition.
– Contributed to US Patent 10,949,353 and improved video activity recognition services.
Software Development Engineer, Computer Vision – Amazon Go
Amazon, Greater Seattle Area
– Designed and developed computer vision systems enabling Amazon Go’s cashierless stores.
– Delivered three major services and contributed to four US patents for Amazon Go.
PhD Candidate
University of Illinois at Urbana-Champaign, USA
– Researched 3D facial modeling and expression recognition from videos (collaborated with Adobe, Cisco).
– Published and contributed to machine learning algorithm advancements in data science.
Summer Intern
Hewlett-Packard Laboratories
– Developed SLAM systems for 3D scene reconstruction with RGB-D data.
– Contributed to US Patent 9,286,717.
Summer Intern
Adobe
– Created algorithms for facial shape modeling and future Photoshop features.
– Collected facial datasets and contributed to four US patents.
Summer Intern
Nuvixa Inc. / Coordinated Science Lab
– Built head and eye tracking algorithms for telepresence and video conferencing.
– Demonstrated technology at CES 2011.
R&D Associate
FPT Corp., Vietnam
– Developed image processing and object recognition modules for robotic vision systems.
How to work with us
We match you directly with global industry experts from our network in hours—not weeks or months.
1
2
3
Share your needs
Choose your talent
Start your risk-free talent trial
Discuss your needs and refine the scope with a Toptal expert.
Get a shortlist of matched talent within 24 hours to review and interview.
Work with your chosen talent for up to two weeks. Pay only if you hire.