Aaron Mcgreevy
Chief Distribution Officer Head Of Sales at Manning & Napier
Columbus, Ohio, United States
Summary
🤩
Rockstar🎓
Top SchoolAaron Mcgreevy is a seasoned distribution and sales executive with over two decades in the investment industry, currently serving as Chief Distribution Officer and Head of Sales at Manning & Napier. He leads multi-channel distribution across Institutional, Taft-Hartley, Intermediary, and Wealth Management, driving revenue growth while shaping firm strategy as an Executive Committee member. Known for building solutions-oriented sales cultures, he pairs deep product and portfolio knowledge with a passion for training diverse talent and serving union construction trades to help members build retirement wealth. His background spans risk analysis to national asset management leadership, and—less expectedly—he contributes machine learning engineering work to open-source AI infrastructure, having implemented efficient embedding caching strategies in the ColossalAI project. Based in Columbus, Ohio, he blends hands-on technical curiosity with strategic sales leadership to grow sustainable, client-focused programs.
6 years of coding experience
7 years of employment as a software developer
Accredited Asset Management Specialist, Investments and Securities, Accredited Asset Management Specialist, Investments and Securities at College for Financial PlanningBachelor’s Degree, Business Administration and Management, General, Cum Laude, Bachelor’s Degree, Business Administration and Management, General, Cum Laude at The University of FindlayAssociate’s Degree, Business Administration and Management, General, Associate’s Degree, Business Administration and Management, General at Owens Community College
Github Skills (11)
caching10
pytorch10
machine-learning10
deep-learning10
python10
large-scale10
distributed-computing10
parallelization9
data-parallelism9
data-parallel9
ai8
Programming languages (2)
Github contributions (5)
hpcaitech/ColossalAI
Aug 2022 - Nov 2022
Making large AI models cheaper, faster and more accessible
Role in this project:
ML Engineer
ML EngineerContributions:19 reviews, 11 commits, 19 PRs in 2 months
Contributions summary:Aaron made several commits focused on the implementation and optimization of a caching mechanism for embedding layers within the colossalai library. They worked on LFU and dataset-based eviction strategies, refactoring existing caching code. The contributions include modifications to the `cache_mgr.py` file, as well as adding tests related to the caching behavior within the `test_cache_embedding.py` file. Further commits involved adding tablewise sharding support for FAW embedding and isolating cache operations to improve maintainability.
aideep-learninghpclarge-scaledata-parallelism
CsRic/blog
Nov 2023 - Jun 2024
Contributions:92 pushes, 1 branch in 7 months
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