Nick Greenquist
Senior Software Engineer @ Google · Machine Learning · Recommender Systems
Hello! I'm a Senior Software Engineer at Google, working on the Google Play Store Personalization team where I help build and scale the recommender systems that connect billions of Android users with their next favorite app or game.
The road here was a bit winding:
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Six summersOcean Lifeguard, Spring Lake, NJMy Baywatch career: six summers guarding the Jersey Shore with Spring Lake Ocean Rescue.
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2012 – 2017Rochester Institute of Technology (BS)BS in Game Design & Development, CS minor. Wrestled four years for the NCAA D3 program where I was team captain and a 3× Academic All-American.
- 💻 2015 – 2018Four SWE Internships
Frontend, backend, and data engineering at eHealth Technologies, GeekHive, Enigma, and Bluecore.
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2017 – 2019New York University, Courant (MS)MS in Computer Science focused on Machine Learning and AI: where recommender systems hooked me and I published my first research.
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2019 – nowGoogleJoined the Google Play Personalization team out of grad school; now a Senior SWE building Play Store recommendation systems for billions of users.
- 👶 2025 – foreverDad
The newest and most important title and role. Everything else I'm into lives further down this page, in Away from the Keyboard.
At the Keyboard — Personal Projects
Production-grade recommender systems: built in PyTorch and deployed live on Streamlit.
Movie Recommender
→Trained on MovieLens 32M · 9,375 movies · ~50k users
↑ 8.7× MRR over the MSE baseline (0.115 vs 0.013)
GitHub ↗Book Recommender
→Trained on Goodreads · 14,753 books · 229k users
↑ 3.4× Hit@10 over the MSE baseline (16.0% vs 4.7%)
GitHub ↗Steam Game Recommender
→Trained on Steam Games Dataset · 5,437 games · 66k users
↑ Wide & Deep ranker: +16% NDCG@10 over retrieval-only
GitHub ↗Amazon Games Recommender
→Trained on Amazon Video Games · 16,882 games · 50,626 users
↑ Sampled NDCG@10 0.519 — within 3.2% (relative) of published SASRec’s 0.536
GitHub ↗Featured Blog Posts
See all posts →$200 vs $200k: Generating Item Features With an LLM Instead of Hand Tagging
→A controlled two-tower recommender experiment on MovieLens 32M and what it means for a team setting up recommendations with no tagging budget.
Taming popularity bias in recommender systems with logit adjustment
→My two-tower recommender kept handing everyone the same blockbusters. Here's how one term in the loss got it surfacing the niche films that actually fit each user's taste.
Building a Two-Tower Deep Learning Movie Recommender System in Pytorch (from scratch)
→Building a two-tower deep learning movie recommender system from scratch in PyTorch, end to end.
Publications
See all publications →Peer-reviewed research in recommendation systems.
Pyrorank: A Novel Nature-Inspired Algorithm to Promote Diversity in Recommender Systems
→Doruk Kilitcioglu, Nicholas Greenquist & Anasse Bari · ICSI 2023 · Jul 2023
GPU Accelerated Matrix Factorization for Recommender Systems
→Doruk Kilitcioglu, Nicholas Greenquist, Mohamed Zahran & Anasse Bari · ICBDA · Apr 2021
GKB: A Predictive Analytics Framework to Generate Online Product Recommendations
→Nicholas Greenquist, Doruk Kilitcioglu & Anasse Bari · ICBDA · Mar 2019
Photography
See full portfolio →Whenever I have a free moment I'm out with my camera. A few favorites gallery links below.
Recognition
G1 (Globo) — Featured Story
→Featured for wildlife photography from the Pantanal, Brazil (2022).
New Jersey Monthly — Magazine Cover Search Competition
→Honorable Mention for 'New Residents of Cape May,' selected from 1,509 submissions (2025).
Atlantic Highlands Arts Council — Juried Gallery (Sold)
→Piece selected for the 'Black & White & Monochrome' juried exhibition and sold (2022).
Away from the Keyboard
Reading, fitness, travel and above all: being a dad.
New Dad: I became a dad this past year. It is easily the most important thing that's happened in my life. Most of my time and energy these days goes into being the best father I can be.
Travel: We've kept traveling even as new parents (at least trying to). Our son has already been to Cancun, Mexico and to Campo Grande, Brazil for his first birthday and to meet his Brazilian family. Next up is a summer camping trip with our trailer. I keep my travel map up to date here.
Fitness: Old habits from wrestling die hard; physical fitness is still an important part of my routine, and the best way I know to clear my head. I lift weights 5-6x a week and try to walk 10k+ steps a day.
Books: I'm always reading or listening to audiobooks. Check out my Goodreads to see what I've recently finished and what I'm currently reading.
Pokémon: Having a kid sent me straight back to my childhood: I've gotten back into collecting Pokémon cards with the hope of passing the hobby on to my son when he's ready. My goal is to complete the Pokédex (one card for every one of the 1000+ Pokémon) and you can follow my progress in this live tracker.
Links
Projects
→Recommender systems (in depth writeups).
Blog
→Thoughts on machine learning and projects.
Publications
→Peer-reviewed research on Google Scholar.
Photography
→Wildlife and travel photography portfolio.
Travel Map
→Everywhere I've been on Earth.
Wrestling
→What it took and what it gave back.
Education
→Every course I've taken.
Reading
→My full reading history on Goodreads
Resume
→PDF (kept current).
GitHub
→Code and side projects.
Professional and career details.
Wildlife, travel, and everyday moments.
Contact
→Send me a message.