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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¶

If you want me to participate/speak at your event/podcast, feel free to reach out to me via email
You can now book a 1:1 Career Mentorship Session via Topmate

Publications¶

📙 LLMOps: Managing Large Language Models in Production, 🚀 In Bookshops Near You and Amazon - July 2025
📙 What is LLMOps, O'Reilly Publications, 2024 - Paperback available at Data + AI Summit, 2024 by Databricks
Report - Data Governance for Analytics and Generative AI, Slides, 2025
Report - Large Language Models - Sector Deep Dive with Laconia Capital, August 2023
The Costly Dilemma: Are Large Language Models the Pay-Day Loans of Machine Learning, June 2023
Arena: A General Evaluation Platform and Building Toolkit for Multi-Agent Intelligence, Accepted for poster presentation at AAAI 2020
Problems & Challenges in AutoML, 2019

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¶

February 2025 Reviewer for Proceedings, Advances in Approximate Bayesian Inference (AABI) co-hosted at ICLR 2025
June 2024 Reviewer for Empirical Methods in Natural Language Processing(EMNLP), 2024
February 2024 Reviewer for the 66^th Association of Computational Linguistics (ACL) Conference, 2024
March 2024 Reviewer for AABI 2024 (Advances in Approximate Bayesian Inference)
October 2023 Reviewer for NeurIPS Workshop: I (Still) Can't Believe It's Not Better
September 2023 Reviewer for Reviewer for DGM4H NeurIPS 2023
March 2023 Reviewer | Fifth Symposium on Advances in Approximate Bayesian Inference (AABI 2023)
September 2022 Proposal Reviewer, PyData NYC
September 2021 Reviewer for NeurIPS Workshop: I (Still) Can't Believe It's Not Better
August 2021 Research Mentorship | Association for Computational Linguistics
November 2018 Area Chair - AutoML | NeurIPS 2018
May 2018 - Sep 2018 Organising Committee Co-Chair, Pydata Los Angeles
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!

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.