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Hi, I’m Abi. I am the founder of Abide A.I., machine learning research engineer and an author.
My work focuses on building intelligent systems that scale. Over the past decade, I’ve designed and deployed production-grade machine learning pipelines across domains like recommender systems, speech synthesis, time-series forecasting, and automated data labeling for both audio and video.
I’m especially interested in the challenges that emerge at scale: memory optimization, distributed training, GPU engineering, and the future of multi-agent systems. I’m currently advancing research in:
- Reflective intelligence in AI agents
- Self-healing protocols in distributed multi-agent environments
- GPU systems for large-scale training of language models
Previously, I was a Visiting Research Scholar at UCLA’s Cognitive Systems Lab under Dr. Judea Pearl, where I focused on intelligent agents with a focus on AutoML, Emotion Recognition, Causal Inference and Multi-Agent learning.
I’ve also served as a reviewer for leading ML and NLP venues like NeurIPS, ACL, EMNLP, and AABI, and I care deeply about helping engineers understand the low-level systems knowledge needed to train and deploy advanced AI models reliably.
Books & Courses¶
I am the author of two upcoming books:
- LLMOps: Managing Large Language Models in Production (O'Reilly, shipping August 2025- pre-order now on Amazon)
- GPU Engineering for AI Systems (Packt Publishing, releasing Autumn 2026)
The best way to stay updated with my research work is either through my public talks or the newsletter.
Collaboration¶
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If you want me to participate/speak at your event/podcast, feel free to reach out to me via email
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You can now book a 1:1 Career Mentorship Session via Topmate
Publications¶
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📙 LLMOps: Managing Large Language Models in Production, 🚀 In Bookshops Near You and Amazon - July 2025
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📙 What is LLMOps, O'Reilly Publications, 2024 - Paperback available at Data + AI Summit, 2024 by Databricks
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Report - Data Governance for Analytics and Generative AI, Slides, 2025
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Report - Large Language Models - Sector Deep Dive with Laconia Capital, August 2023
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The Costly Dilemma: Are Large Language Models the Pay-Day Loans of Machine Learning, June 2023
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Arena: A General Evaluation Platform and Building Toolkit for Multi-Agent Intelligence, Accepted for poster presentation at AAAI 2020
Social Calendar¶
Upcoming¶
- August 21, Speaker, Debugging and Monitoring LLMs in Production, Infrastructure & Ops O'Reilly Superstream: AI-Driven Operations and Observability
- July 19, Speaker, Lightening Session, LLMOps: Roles and Career Transitions, Maven
June 2025¶
- June 24, Speaker, Monitoring RAG Pipelines, DataCamp Public Webinars
- June 4, Speaker, Lisbon Tech Connect | AI edition
- June 7, Speaker, AI Horizons, UPTEC, Porto
May 2025¶
- 🆕🚀 May 13 - Speaker, Observability in LLM Pipelines, Open Data Science Conference (ODSC) East 2025, Boston - Slides
March 2025¶
- 🆕🚀 Mar 20 - Invited Talk, Evaluating LLMs: From RAG Pipelines to Advanced Reasoning, organized by Embrace.ai, Lisbon (Portugal) - Slides
January 2025¶
- Guest Lecture: Serverless LLM Deployment for Cloud Engineering for Python Developers Course by Eric Riddoch, MLOps Club
Past
2024¶
- Nov 19 - Panelist, Xtreme Python Conference 2024
- Nov 12 - Panelist, Ask the Experts: LLM Engineering
- Nov 11 - Speaker, Accelerate Your AI Workflows - Mastering GPU Strategies, Generative AI in Action Conference
- Oct 5 - Speaker, Data Management for LLMs, Data Engineering And Machine Learning Summit 2024
- Oct 3 - Guest Lecture, Evaluations for MultiAgent Systems, Multi-agents Course by Aggregate Intellect
- Apr 26 - Podcast Guest, Adventures in Machine Learning
- Apr 24 - Speaker, Deploying and Managing LLMs in Production for O'Reilly Events
- Apr 17 - Speaker, SecOps for LLMOps at NatWest Bank, U.K.
- Apr 19 - Speaker, The LLM Summit 2024
- Mar 20 - Speaker: AI and Other Hot Takes at AI Tinkerers, Ottawa, Canada
- Mar 16 - Speaker: Productionizing LLMs: LLMOps - AI X Entertainment Hackathon, CIC Tokyo, Japan
- March 8 - Speaker: 5 min interviews for Hopsworks with Rik Van Bruggen
2023¶
- Nov 8 - Whats New in Data podcast with John Kutay
- Oct 26 - Speaker, Laconia Capital LP Event - LLMOps with Abi Aryan (Privately Hosted by Geri Kirilova and Jeffrey Silverman )
- Oct 13 - Presented a workshop on Productionizing LLMs, Packt Publication Conference
- Oct 10 - Presented a talk on Domain adaptation and fine-tuning for domain-specific LLMs, AI Engineer Summit
- Sept 20 - AMA on LLMOps at Deep Learning Daily organized by Deci.ai
- Aug 29 - Event Chair for Building AI Agents with LLMs Event - O'Reilly
- July 7 - Gave a talk on Cost Modelling for LLMs at the LLM Projects Workshop
- July 7 - Talked about Self-Learning and Growth for careers in Data and MLOps at Women in Data Podcast
- July 6 - Talked about Fune-Tuning and Evaluations for LLMs at What's the BUZZ? with Andreas Welsch
- June 15 - Moderating the panel on LLM Evaluations at LLMs in Production Conference II by MLOps.Community
- May 4 - Speaker at LLMs Demsytified Webinar with Chris Brousseau, Data Scientist at MasterCard
- April 26 - Speaker at Large Language Models in Production Twitter Spaces with Christine Yuen, Co-Founder and Head of Engineering at Shakudo.io, hosted by Sabrina Aquino
- Co-Host MLOps Community Podcast talking about
- Why is MLOps Hard in an Enterprise with Maria Vechtomova & Basak Eskili, Machine Learning Engineers at Ahold Delhaize
- Large Language Model at Scale with Nils Reimers, Director of Machine Learning at Cohere
- ML Scalability Challenges with Waleed Kadous, Head of Engineering at AnyScale
- AI and the Future of Database Optimization with Alex Debrie, Author of The DynamoDB Book
- Challenges of Deploying ML Models on Edge Devices with Jason McCampbell, Chief Architect at Wallaroo
- PeopleOps in MLOps with Shalabh Chaudri, Head of Customer Success, Union AI
- ML in Production with Jean-Michel Daignan, Data Scientist at Ubisoft
- Multilingual Programming with Rodolfo Núñez, Senior Machine Learning Engineer at Entel
2022¶
- Co-Host MLOps Community Podcast talking about
- Foundational models with Alex Ratner, Founder and CEO of Snorkel
- Managing Machine Learning Projects with Simon Thompson, Head of Data Science, GFT Technologies
- HCI for MLOps Infra Companies with Murtuza Shergadwala, Senior Data Scientist, Fidder.ai
- What is MLOps with Niklas Kühl, Managing Consultant for Data Science at IBM
2021¶
- March: Delivered a workshop on Full Stack Deep Learning at Women Who Code Los Angeles
- Hundred other Women Who Code London, LA, SF, NYC events through 2016 - 2021 that I don't remember at the moment, ha!
2020¶
- August: Presented a technical workshop on Natural Language Processing (NLP) Hands On! at MLNerdie Los Angeles
2018¶
- Delivered a workshop on A Hands-On Application of Causal Methods in Python at PyData Los Angeles
- Presented a talk on Big Problems at the Heart of Machine Learning at PyData Los Angeles
Volunteering¶
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February 2025 Reviewer for Proceedings, Advances in Approximate Bayesian Inference (AABI) co-hosted at ICLR 2025
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June 2024 Reviewer for Empirical Methods in Natural Language Processing(EMNLP), 2024
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February 2024 Reviewer for the 66th Association of Computational Linguistics (ACL) Conference, 2024
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March 2024 Reviewer for AABI 2024 (Advances in Approximate Bayesian Inference)
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October 2023 Reviewer for NeurIPS Workshop: I (Still) Can't Believe It's Not Better
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September 2023 Reviewer for Reviewer for DGM4H NeurIPS 2023
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March 2023 Reviewer | Fifth Symposium on Advances in Approximate Bayesian Inference (AABI 2023)
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September 2022 Proposal Reviewer, PyData NYC
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September 2021 Reviewer for NeurIPS Workshop: I (Still) Can't Believe It's Not Better
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August 2021 Research Mentorship | Association for Computational Linguistics
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November 2018 Area Chair - AutoML | NeurIPS 2018
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May 2018 - Sep 2018 Organising Committee Co-Chair, Pydata Los Angeles
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Mar 2016 -Aug 2021 Director, Women Who Code Los Angeles
Top Tweets & Threads¶
While I am on Twitter, LinkedIn as well but I do not promise to post and be active there.
Media¶
October 2024¶
I was featured on the Times Square Billboard by Topmate!
Newsletter¶
Interested in hearing about Data Infrastructure, ML Systems, and new startups/research papers/tools in the ML and LLMOps space?
I send out a newsletter called ModelCraft. Feel free to sub.