Production AI engineering, industry education, and ecosystem leadership.
I'm Jigyasa Grover (pronounced jig-YAH-sah GROH-ver)—a San Francisco–based Machine Learning Engineer, Agentic AI educator, author, and advisor.
Bridging production scale with practical clarity
I currently serve as a Machine Learning Engineer (Tech Lead — Rider Personalization & Ranking) at Uber, leading multi-task ranking and user representation models across 500+ cities alongside 0→1 internal agentic developer tooling.
Previously, I led AI & Research at Bordo AI, built a 0→1 feature store and ads bidding engine at Faire, owned sub-50ms billion-request ads ranking at Twitter (X), and worked at Meta, alongside completing my M.S. in Computer Science (AI) at UC San Diego, attending the Cornell, Maryland, Max Planck Pre-doctoral Research School (CMMRS) in Germany on a full scholarship, and earning research and conference grants from the Government of Canada (Mitacs), Government of Norway, The Linux Foundation, and Facebook (Grace Hopper Scholar). (See full career & research timeline →)
Beyond my day-to-day engineering work, I lead Afterdays—my independent AI advisory, training, and speaking practice partnering with 30+ startups, enterprises, and venture funds—and serve on the Google Developer Advisory Board (gDAB) alongside Google Developer Expert (AI/ML) recognition. I was featured on the Google I/O main keynote stage and in Google's official Gemini Omni Flash launch, co-authored Sculpting Data for ML (95+ citations), and have trained 50,000+ engineers and leaders through LinkedIn Learning and corporate programs with Morgan Stanley, FedEx, Accenture, Roblox, Silicon Valley Security Group, and AI Aspire.
Advisory boards & community leadership
Advising Google engineering and DevRel leadership on developer platforms, Firebase Studio, SDLC agents, and AI ecosystem strategy.
5-year AI/ML GDE featured on the Google I/O main stage, Google's Gemini Omni Flash launch video, Google Developers' AI Agent Bake Off, and Google Cloud Tech documentary; Google Cloud BI Council member and Enterprise Design Partner.
Consulted and advised 30+ teams across Google, Meta, Apple, Microsoft, Anthropic, Amazon Fresh, Spotify, Adobe, Grammarly, Figma, Atlassian, Coinbase, Remitly, Superhuman, Windsurf, Base44, HP, Innodata, Diem AI, Bezoku AI, Okareo, Optica Labs AI, BackOps AI, Founders Circle Capital, and Capital Hill Ventures.
AI Assurance Council, World Economic Forum Global Shapers (Palo Alto), World Summit AI Americas Ambassador, Corinium Global Intelligence, VigiTrust, AI Forum, Pacelearn, Goanna Collective, and Las Positas College.
GitHub Arctic Code Vault Contributor (74+ public repos, 180+ authored PRs across FOSSASIA, Loklak, Hashkat & Loris); credentialed Linux Foundation (OSS NA & Europe) & ACM Tapia Program Committees; PyCon US Financial Aid Co-Chair (3 yrs) & PyBay Chair; Women Who Code Director (grew chapter 10 → 10K+); Apache & PSF contributor; O'Reilly & Packt Reviewer.
Frequently asked questions
Who is Jigyasa Grover?
Jigyasa Grover is a San Francisco–based Machine Learning Engineer at Uber (Tech Lead for Rider Personalization & Ranking), 13× AI and Open Source award winner, Google Developer Advisory Board member, LinkedIn Learning instructor, and co-author of Sculpting Data for ML.
What is her engineering background?
Before Uber, she led AI & Research at Bordo AI, built a 0→1 feature store and ads bidding engine at Faire, owned sub-50ms billion-request ads ranking at Twitter/X, and worked at Meta, alongside completing her M.S. in CS (AI) at UC San Diego and attending the Cornell, Maryland, Max Planck Pre-doctoral Research School (CMMRS).
How can founders, organizers, or brands work with her?
Submit an inquiry on Work With Me, book a 1:1 consultation via Intro or Topmate, or scope developer brand campaigns via Passionfroot or Naano.