Joe Muddle
Machine Learning Developer|Computer Vision Expert
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Über
I am an English speaking machine learning/computer vision developer with 2 years of professional experience. I have developed machine learning products at every stage of the product life cycle, from inception to market. With my experience as a machine learning initiative lead at a small start up company, I have worked with a number of different clients from different sectors and industries, including the public sector/government clients.
I have particular expertise in computer vision, in which I am pursuing a PhD in my free time. I have developed products and research using tensorflow, pytorch, and a number of other technologies (further detailed in my CV). I am a British Citizen seeking employment in Vienna.
Berufserfahrung
Machine Learning Engineer - Distributed Analytics Technologies - December 2021-March 2023
- Lead on AI initiatives
- Worked with range of clients from small startups to large companies - tailoring solutions to clients’ needs
- Technical and research experience; reading and implementation of academic research
- Creation of products using Pytorch and Tensorflow, and relevant libraries for computer vision and AI
- Delivering technical presentations on research
- Experience writing grant proposals for research and development
Machine Learning Engineer - AWL, Inc - September 2021-December 2021
- Worked in neural network R&D team
- Created new neural network backbone architectures
- Worked within Agile software development environment
Data Science Intern - Banco Agromercantil - June 2020-August 2020
- Data analysis and visualisation on client data
Ausbildung
PhD Computer Science (distance learning, completing in free time) University of Portsmouth - October 2022-Present
- Project titled “developing AI technology for the identification of ocular disease”
- Developing computer vision techniques for medical image analysis
- Focus on few-shot learning and image segmentation
- Supervised by Dr Dongxu Gao
- Learned fundamentals of computer science and artificial intelligence
- Final project “generative cooperative networks for creativity” received grade of 81%, one of the highest in the year
- Gained experience in a research setting