Richard Hamnett
Board Technology Advisor at M1NTY
Manchester, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolRichard Hamnett is a technologist and founder with over a decade of experience building VC-backed and exited companies across contact centres, massively scalable big data & analytics, and machine learning. He currently leads SmarterDemo and M1NTY, advises Arrow Global Group as CTO, and invests with Manchester Angels, combining operator experience with active angel mentoring. As co-founder and long-time CTO of ResponseTap he scaled products to commercial traction before moving into founding and advisory roles. He contributes to open-source ML projects — notably improving data-preprocessing and training for Mozilla's DeepSpeech (an on-device speech-to-text engine) and refining reinforcement-learning tooling in TensorTrade — demonstrating hands-on ML engineering skill. Comfortable bridging research and production, he focuses on pragmatic model training, data pipelines and scalable analytics platforms. Based in Manchester, he blends startup grit with investor perspective across the North-West tech ecosystem.
10 years of coding experience
13 years of employment as a software developer
BSc, Computing, BSc, Computing at The Manchester Metropolitan University
Github Skills (10)
speech-to-text10
tensorflow210
machine-learning10
tensorflow10
python10
mozilla-deepspeech10
reinforcement-learning10
neural-networks9
jupyter-notebook9
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, 19 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.
deployingraybacktesting-trading-strategiesreinforcement-learningagents
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.
speech-recognitiontensorflowreal-timeraspberry-pion-device
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