Neil Patel Email & Phone Number

Menlo Park, Ca, Us

May 2024+ : Generative AI ResearchLLAMA pretraining -- Multi-modal and LLM pretraining data ingestion -- model batch inferenceLLAMA Training -- Evaluations ---------------------------------------------------------------April 2020- May 2024 : Spatial AI @ Oculus/Meta Reality Labs-------------------------------------------------------Feb 2019 - April 2020: Family of Apps, Growth ML Ground Truths* Worked on understanding people-level versus user-level behavior across our family of apps, focusing on ground truth for ML models and SEC reporting* Rebuilt systems — reduced runtime from 16 hours to 15 minutes, cut storage use 100x, and saved 50x compute * Reduced statistical uncertainty from +/- 4% to +/- 1% * Redesigned model resulting in a topline, SEC reported people-level growth in the 10’s of millions

Menlo Park, Ca, Us

*running point on team, org, and XFN infrastructure and tooling *growing my previously built 0->1 team infra into orgwide standard with company-level adoption*Went through the Pro-M program in preparation to formally transition to tech lead manager

Menlo Park, Ca, Us

* Cross-Facebook Reality Labs initiatives like Computer Vision privacy, telemetry re-architecting and anonymization, and improving the state and complexity of CV Benchmarking tooling* Mentoring junior engineers and interns* Led v-team to develop a cross-org process and tooling around monitoring Oculus software release rollouts + thoughtful A/B testing

Menlo Park, Ca, Us

Focused on the entire product lifecycle of computer vision research -> production ready ARVR tech -> current/future consumer devices/features.I'm currently focused on 3 major things: * algorithm benchmarking around environment perception/mapping/localization -- building tooling that speeds up algorithm iteration times and helps understand when and why/where performance is regressing* Product Launch & Analytics: When we build features around these algorithms, how do we make them great/indispensable? How do they perform over time? Are they succeeding?* Writing frameworks/building tools to make the basic/repetitive/critical parts of the first 2 bullets easy/scalable/headcount-less so that I can focus on the super exciting stuffSome highlights:* Built tooling to enable Eng teams/features across Oculus to define and monitor User Metrics (Growth Accounting, retention, regressions, etc), code and analytics team free, to enable analytics bandwidth to be used more effectively* Working on an internal framework to enable out-of-box algorithm benchmarking without analytics team* Developed private by design telemetry and performance/success metrics for hardware and software products* Internally published several Quest 2 launch unblocking statistical analyses * Worked with Product teams to define and design launch plans for released and upcoming products/features* Worked with Design teams to generate and iterate on hypotheses for various products (e.g. Guardian, Hand-tracking) to investigate hunches that significantly increased user adoption and retention

helping friends build tools for our busiest friends and family membersReach out to learn more!

Menlo Park, Ca, Us

Python + SQLProduct Analytics around confidential Instagram feature -- we really cared about retention on this one and it was exciting to be an intern participating in "trying to shift all these levers" and "doubling down on xyz"

North Chicago, Illinois, Us

Extended Python pipeline to cover more experiments and AWS services Piloted Infrastructure as Code solution for the oncology team using Ansible and Terraform

* Utilized OpenCV and convolutional neural nets for image recognition, modification, and classification * Built an image classification pipeline using Python, OpenCV, and TensorFlow* Devised/Computed a list of critical features for accurate machine learning pipeline results* Analyzed 2 years of tweets to discover trends and customer needs with Python, NLTK, and numpy *Proposed, designed, and built a biometric entry system + app using the iOS NoPass SDK.

North Chicago, Illinois, Us

Built Python pipeline using Boto3 to automate workflows for data-crunching biotechnology research running across AWS services

Washington, Dc, Us

* Proposed pilot to develop a full stack service recommender using Python/Django * Deployed a recommender system using the python machine learning package graph lab* Designed and began building a Rest API around the recommender system* Developed a web scraper using BeautifulSoup; Natural Language Processing with NLTK

Irvine, Ca, Us

* Developed interconnected Hearthstone gameplay/player and server metrics -- then built an internal Python/Django webpage for real-time internal monitoring* Wrote Ansible playbook to check readiness of servers, used across all of Hearthstone (20 million players) * Wrote several Puppet manifests for configuring various aspects of Hearthstone Servers * Participated in several hotfixes, culminating in one where I ran the global deployment (with a nervous team looking over my shoulder!) * Dockerized several test cases to propose the containerization of several Blizzard websites

Master Of Science - Ms, Computer Science

Bachelor’S Degree, Computer Engineering

High School