Ikechukwu Uchendu
AI Trainer - Machine Learning Expert at Handshake AI Fellowship
Boston, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolIkechukwu Uchendu is an AI trainer and machine learning expert with a decade of experience building and stress-testing intelligence systems across industry and academia. Currently a PhD student at Harvard, he specializes in evaluating and adversarially probing large language models for computer science reasoning, AI alignment, and autonomous ML safety. His background includes research and residency roles at Google, DeepMind, and Hands-on engineering internships at LinkedIn, Microsoft, and Humana, giving him a rare blend of production software engineering and cutting-edge RL/agent research. He has designed domain-specific prompts and adversarial benchmarks to reveal subtle failure modes in LLMs and documented rogue agent behaviors during autonomous workflows. Comfortable moving between low-level systems (databases, Spark, microservices) and high-level model evaluation, he leverages practical engineering to close the loop on model robustness. Based in Boston, he pairs rigorous academic training with a pragmatic focus on making AI systems safer and more reliable in real-world applications.
10 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Harvard UniversityMaster of Science - MS Computer Science, Master of Science - MS Computer Science at Michigan State UniversityHighschool Diploma, Highschool Diploma at Wylie E. Groves High School
English
Github Skills (14)
keras10
deep-learning8
machine-learning8
tensorflow8
multiplication2
penguin2
ruby2
dub2
printf1
linuxbrew1
linux1
deep-reinforcement-learning1
xorg1
reinforcement-learning1
Programming languages (5)
Github contributions (5)
Farama-Foundation/A2Perf
Aug 2023 - Sep 2024
A2Perf is a benchmark for evaluating agents on sequential decision problems that are relevant to the real world. This repository contains code for running and evaluating participant's submissions on the benchmark platform.
Contributions:9 releases, 1 review, 1 PR in 1 year 1 month
Farama-Foundation/a2perf-benchmark-submission
Nov 2023 - Aug 2024
Contributions:1 review, 1 PR, 2 pushes in 9 months
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