Richard Hamnett
Board Technology Advisor at MOJO CX
Manchester, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolRichard Hamnett is a technologist, founder and board-level advisor with over a decade of experience building and scaling VC-backed companies in contact centre analytics, big data, machine learning and blockchain. He co-founded and led ResponseTap to acquisition and now advises startups and corporates (MOJO CX, Arrow Global) while investing and mentoring through Manchester Angels. Hands-on in ML and open source, he has contributed to notable projects like Mozilla DeepSpeech and the TensorTrade reinforcement-learning framework, improving data pipelines and reward schemes for robust agents. Richard combines operator experience as a former CTO with active investing and advisory roles across the North-West, and is known for turning production ML prototypes into scalable commercial products.
11 years of coding experience
13 years of employment as a software developer
BSc Computing, BSc Computing at The Manchester Metropolitan University
Github Skills (9)
speech-to-text10
machine-learning10
tensorflow10
python10
mozilla-deepspeech10
reinforcement-learning10
jupyter-notebook9
neural-network9
pandas8
Programming languages (17)
Github contributions (5)
tensortrade-org/tensortrade
Oct 2019 - Mar 2022
An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.
Role in this project:
ML Engineer
ML EngineerContributions:12 reviews, 12 commits, 20 PRs in 2 years 4 months
Contributions summary:Richard primarily contributed to the development and improvement of the `tensortrade` reinforcement learning framework. They modified the code for the `Stream` object, enhanced the `SimpleProfit` reward scheme, fixed multiplication errors within the environment, and updated example notebooks. These contributions suggest a focus on refining existing features and improving the framework's functionality, including the addition of a missing library.
reinforcement-learningtrading
mozilla/DeepSpeech
Sep 2019 - Feb 2020
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
Role in this project:ML Engineer
ML EngineerContributions:5 commits, 10 PRs, 50 comments in 5 months
Contributions summary:Richard primarily contributed to the data preprocessing pipeline and model training configuration for the DeepSpeech project. They created a script to import and process VCTK data, which involved downloading, extracting, and converting audio files and transcripts. Additionally, they modified the model loading mechanism and learning rate initialization, demonstrating involvement in model training and optimization aspects of the project. They also addressed a bug in the transcribe functionality and adjusted the learning rate settings.
gpuraspberry-pispeech-to-textdeep-learningmachine-learning
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