Sam Armstrong
Senior Officer, Private Fundraising Communications
London, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolSam Armstrong is a fundraising and impact reporting professional with a strong academic grounding in conflict, security and development and over seven years of hands-on experience across institutional, trusts & foundations, and community fundraising. Currently at the International Rescue Committee, Sam turns complex programmatic work into persuasive donor-facing proposals, reports and communication assets while coordinating cross-functional teams and editorial timelines. Previously led global programme funding functions at Right To Play UK, managing multi-jurisdictional grant portfolios and helping steer CRM and process transitions. Sam pairs analytical rigor—evident in KPI reporting, compliance-heavy grant management and a merit-distinguished MA thesis—with creative campaign and events experience from roles in digital marketing and events account management. Unexpectedly, Sam also contributes to open-source ML tooling on GitHub, improving framework interoperability in the ivy project, demonstrating a practical curiosity about technical solutions that complement their international development expertise. Based in London, they bring a rare blend of programmatic insight, donor-centric storytelling and operational delivery across complex global funding landscapes.
5 years of coding experience
2 years of employment as a software developer
Master’s Degree, Conflict, Security & Development, Master’s Degree, Conflict, Security & Development at University of Sussex
Github Skills (9)
paddlepaddle10
machine-learning10
model-conversion10
interoperability10
python10
documentation9
deep-learning7
pytorch6
tensorflow6
Programming languages (5)
Github contributions (5)
unifyai/ivy
Nov 2022 - Nov 2022
Convert Machine Learning Code Between Frameworks
Role in this project:
ML Engineer
ML EngineerContributions:24 releases, 176 reviews, 1 commit in 1 day
Contributions summary:Sam's contributions primarily focused on refactoring and improving the `multi_head_attention` module within the `ivy` library. This involved adding type hints, a nestable description, and comprehensive docstring examples. Additionally, the user added a converter function named `from_paddle_module` for converting Paddle layers to Ivy modules, demonstrating efforts to improve framework interoperability and model conversion capabilities. Furthermore, the user made multiple changes in the paddle backend to improve performance and address specific issues, showing active work towards supporting a wider range of frameworks.
machine-learningpythontensorflowpytorchnumpy
Sam-Armstrong/UFC-Almanac
Aug 2021 - Jul 2026
Program for predicting the outcome of UFC using a deep learning model. The data for training this model is scraped from the web.
Contributions:2 PRs, 45 pushes, 5 branches in 4 years 11 months
deep-learning
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