Alexander Miller
Senior Research Engineering Manager, FAIR at Meta
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolAlexander Miller is a Senior Research Engineering Manager at Meta AI Research (FAIR) with a decade of experience building and leading teams at the intersection of deep learning, conversational AI, and reinforcement learning. He led the team behind CICERO, a Diplomacy-playing agent, and has overseen groups working on large language models and automated theorem proving, reflecting a blend of applied ML and theoretical rigor. Early work includes co-founding the ParlAI dialogue platform and contributions to Memory Networks and the bAbI tasks, showing long-standing involvement in dialogue and reasoning benchmarks. He couples hands-on engineering—test automation and module implementations across high-profile Facebook research repos—with people leadership across global FAIR sites. Based in New York, he now directs research into neuromotor interfaces, signaling a shift toward neurotech applications of ML. Colleagues describe him as a manager who moves easily between shipping robust research code and guiding high-impact scientific projects.
10 years of coding experience
6 years of employment as a software developer
Master of Science (MS), Computer Science, Master of Science (MS), Computer Science at New York UniversityBachelor of Arts (BA), Computer Science, Bachelor of Arts (BA), Computer Science at Cornell University
Github Skills (16)
neural-network10
unit-testing10
lua10
torch-hub10
machine-learning10
nlp10
torch-net10
pytest10
python10
testing10
natural-language-processing9
data-processing9
dialogue-systems9
github7
git-repository7
Programming languages (6)
Github contributions (5)
facebookarchive/MemNN
Nov 2016 - Jul 2020
Memory Networks implementations
Role in this project:
ML Engineer
ML EngineerContributions:59 commits, 4 PRs, 56 pushes in 3 years 8 months
Contributions summary:Alexander primarily contributed new code related to "dialog-based language learning" within the "Memory Networks implementations" repository. This involves the implementation of a new Lua module named `memmnet.lua` containing functions and neural network architectures for processing dialogue data. The commits introduce functionalities such as `MeMM_`, `LookUpTable_`, `PrepareNegativeResponse`, and data preparation routines crucial for training and evaluation of memory networks within the dialogue-based learning context. The contributions suggest a focus on building and refining models for this specific task.
implementationsmemoryvisual-recognitionallennlpmemory-networks
facebookarchive/bAbI-tasks
Aug 2016 - Mar 2017
Task generation for testing text understanding and reasoning
Role in this project:Back-end Developer
Back-end DeveloperContributions:5 commits, 1 PR, 3 pushes in 7 months
Contributions summary:Alexander primarily contributed to the back-end logic of the project, focusing on modifications to the stringification and task generation components. They fixed bugs related to wording, implemented changes to improve the accuracy of the generated tasks. Additionally, the user modified the code to utilize torch.class and fixed the logic in the question-generation process.
testingunderstanding
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