"I was able to land an MLE FAANG offer with his reviews and prep material. 10/10 recommend!"
Principal ML Architect
Architecting foundation models at billion-user scale — and equipping the world's engineering teams to put AI to work. Principal ML Lead at Atlassian (ex-Twitter, Attentive, Amazon), AI Faculty at AI Aspire (by Andrew Ng), published author, and advisor across 50+ organizations — reaching millions of developers globally and recognized by the US Government (EB-1) for outstanding contributions to ML.
- Lead
- Atlassian · ex-Twitter, Amazon, Attentive
- Educator
- AI Aspire (Andrew Ng) · Udacity · LinkedIn
- Advisor
- 50+ Orgs · Meta Council · 5.0★ Mentor
- Author
- Sculpting Data for ML · 1,200+ Citations
Featured Work
Partnering with Andrew Ng's AI education ecosystem to equip enterprise engineering organizations to adopt and scale AI — including delivering a 2-week corporate AI training program for Morgan Stanley in New York.
Adopted in DeepLearning.AI's NLP course on Coursera, Google's TensorFlow professional certification program, and the NSF-funded StoryQ curriculum.
Comprehensive course covering model parallelism, DeepSpeed, TensorRT-LLM, and Triton Inference Server.
Designing, building, and deploying production-ready LLM-powered Recommender Systems; featured in the University of Florida Career Hub.
Enterprise AI & microservices module covering LLM chat clients, tool-calling agents (Spring AI, LangChain4j), modular RAG pipelines, and vector search (HNSW, HyDE, re-ranking).
What People Say
"He really has a range of experience and depth of knowledge that only a select few engineers can contain in one head. Could not recommend more!"
"Rishabh is an exceptionally knowledgeable mentor in the AI/ML space... Under his mentorship, I successfully completed two research papers and currently have a third paper in progress."
Latest Updates
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Oct 2026
Delivered a 2-week corporate AI training program for Morgan Stanley in collaboration with AI Aspire (by Andrew Ng). New York, NY
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Oct 2026
Partnering via Afterdays with AI Aspire, Andrew Ng's AI advisory & education organization, to help enterprises build practical applied ML and AI engineering capabilities (announcement).
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Sep 2026
Presented "When NOT To Use an Agent: Choosing Between Workflows, Services, and Agent Systems" with Jigyasa Grover at AGNTCon + MCPCon Europe 2026. Amsterdam, Netherlands
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2026
Launched Enterprise AI, RAG & Agents curriculum ("Intelligent Backends with RAG & Chat Models" — Spring AI, LangChain4j, HNSW & HyDE vector search) on Udacity.
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Jul 2026
Hosted a fireside chat on "Industrial AI & Computer Vision Moats" with Reza Zadeh at Goanna Builders Day. San Francisco, CA
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Jul 2026
Featured Instructor for "Applied Agentic AI", "Building Vertical AI Agents", and "Building AI Agent for Retail" at Interview Kickstart.
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Jul 2026
Presented "The New Technical Debt: Data" at SciPy 2026.
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Jul 2026
Presented "Making LLM Evaluation Reproducible in Python" with Jigyasa Grover at EuroSciPy 2026.
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May 2026
Delivered a keynote titled "When NOT to use an agent: Lessons from systems that didn’t want autonomy" with Jigyasa Grover at Driving AI 2026. Copenhagen, Denmark
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Mar 2026
Guest speaker at Interview Kickstart, leading deep-dive sessions on Agentic RAG and Structured Prompting.
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Feb 2026
Presented "AI Showdown: Open Source Tools for LLM Face-Offs" at MLCon San Diego.
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Feb 2026
Co-presented "AI as a Cog in the Machine: Transforming Unstructured Data" at MLCon San Diego with Jigyasa Grover.
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Jan 2026
My LinkedIn Learning course on "Building LLM-Powered Recommendation Systems" (GitHub) is live and featured in the University of Florida Career Hub.
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Oct 2025
My online course on LLM Inference Optimization is live on Udacity.
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Sep 2025
Joined Atlassian as Principal ML Engineer / Tech Lead — driving critical LLM/SLM pre-training, fine-tuning, and generative personalization at scale for Atlassian Intelligence.
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Sep 2025
Co-presented "Guarding the LLM Galaxy: Security, Privacy, and Guardrails in the AI Era" with Jigyasa Grover at KWSQA Targeting Quality 2025. Cambridge, Canada
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Aug 2025
Presented "Open Source Tools for LLM Face-Offs" with Jigyasa Grover at AI Dev 2025 (video). Amsterdam, Netherlands
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Jun 2025
Presented "Guarding the LLM Galaxy" with Jigyasa Grover at Open Source Summit 2025 (video). Denver, Colorado
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2025
Serving as a Reviewer for ACL 2025 (via ACL Rolling Review) and Program Committee Member for RecSys 2025.
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Jan 2025
Invited to serve on Meta's Research Advisory Council.
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Jan 2025
Serving as a Program Committee Member at SIGIR 2025.
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Dec 2024
Expert commentary on AI alignment and safety published in The Sun.
- Oct 2024
Full Archive (2018–2024)
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Sep 2024
Published Introduction to Maximum Likelihood Estimates with TowardsDataScience.
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Sep 2024
Published What is Generative AI? with Analytics Vidhya.
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Sep 2024
Published Unlock Hyper-Personalized Advertising with Generative AI with Analytics Vidhya.
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Aug 2024
Published Introduction to Support Vector Machines with TowardsDataScience.
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Jul 2024
Talk on Sculpting Data for ML & Guarding the ML Galaxy with Jigyasa Grover at Developer Week. Nuremberg, Germany
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May 2024
Serving as a Program Committee Member for CIKM 2024.
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Apr 2024
Talk on 'Guarding the ML Galaxy' at Open Source Summit. Seattle, US
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Apr 2024
Talk on Sculpting Data for ML with Jigyasa Grover at Update Days: Implement AI. Prague, Czechia
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Jan 2024
Serving as a Program Committee Member for SIGIR 2024.
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Dec 2023
Serving as a Program Committee Member for TheWebConf 2024.
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Sep 2023
Speaking at Salon de la Data 2023 on Sculpting Data for ML. Nantes, France
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Jul 2023
Thoughts on AI alignment and safety published in The Sun.
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Jun 2023
Book chapter "Keeping it Low-Key: Modern-Day Approaches to Privacy-Preserving Machine Learning" published in Springer.
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Jun 2023
Thoughts on the importance of Data as a Service published in BuiltIn.
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Jun 2023
Serving as a Program Committee Member for CIKM 2023.
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May 2023
Speaking at Data Innovation Summit 2023 on Sculpting Data for ML. Virtual
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Mar 2023
Interview on Sculpting Data for Machine Learning published by Hyperight.
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Feb 2023
Thoughts on Digitization in retail industry featured in Colliers.
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Feb 2023
Publication "Sarcasm Detection using News Headlines Dataset" published in journal AI Open.
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Jan 2023
Serving as a Program Committee Member for SIGIR 2023 and ICWSM 2023.
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Nov 2022
Thoughts on AI changing Art Industry featured in Hyperallergic.
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Nov 2022
Thoughts on how DALL-E works featured in Interesting Engineering.
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Oct 2022
Expert commentary on AI tools for art generation featured in Lifewire.
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Oct 2022
Thoughts on rising demand of Machine Learning skills featured in Reworked.
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Oct 2022
Expert commentary on Future of AI in acting featured in Lifewire.
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Oct 2022
Serving as a Program Committee Member for TheWebConf 2023.
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Jul 2022
Serving as a Program Committee Member for ICDM 2022.
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May 2022
Serving as a Program Committee Member for RecSys 2022 and TORS 2022.
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Apr 2022
Speaking at PyCon 2022 on Sculpting Data for ML. Salt Lake City, UT
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Mar 2022
Serving as a Program Committee Member for ECML-PKDD 2022.
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Mar 2022
Speaking at RvaTech Data Summit on Sculpting Data for ML. Richmond, VA
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Feb 2022
Speaking at Re-Work Enterprise AI Summit on scaling Tweet Reply ranking to 10M+ QPS. San Francisco, US
- Jan 2022
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Jan 2021
Co-authored Sculpting Data for ML book with Jigyasa Grover.
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Dec 2019
Research paper on Addressing Marketing Bias in Product Recommendations selected for oral presentation at WSDM'20.
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Nov 2019
Ranked in Top 20 dataset contributors on Kaggle.
- Jul 2019
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Jul 2019
Joined Twitter as an ML Engineer in the Timelines Quality team.
- Jun 2019
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May 2019
Research paper with Mengting Wan, Ndapa Nakashole and Julian McAuley accepted at ACL'19.
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Jul 2018
Research paper with Mengting Wan and Julian McAuley accepted at RecSys'18.