FLAGSHIP / OPEN SOURCEClaude LinkedIn Assistant
A job-search operating system that discovers roles, scores fit, maintains a transparent tracker, and prepares human-approved outreach.
205STARS
46FORKS
STAFF AI/ML ENGINEER @ SNOWFLAKE
SAN FRANCISCO BAY AREA
FARZAM
HEJAZI.
I build generative AI products, open-source agents, and learning systems for the physical world.
AI / MLFOCUS
GENERATIVE AI
AGENTIC SYSTEMS
PHYSICAL AI
205STARS ON THE FLAGSHIP PROJECT
206RESEARCH CITATIONS
17PUBLISHED WORKS
4.3KLINKEDIN FOLLOWERS
01 / SELECTED WORKUSEFUL AI.
USEFUL AI.
BUILT TO SHIP.
Products and open-source systems designed around real workflows, not technology demos.
FLAGSHIP / OPEN SOURCEVIEW PROJECT
02DESKTOP AI
Electron · React · Native audio · Local models
AnswerCue
A cross-platform interview copilot for preparation, local transcription, real-time answer support, and post-interview memory.
7 starsOPEN
03AGENTIC RESEARCH
Claude Code · Alpaca · Human-controlled trades
Investment Assistant
A rules-over-emotion workspace that turns plain-English investing strategies into daily checks and evidence-backed research memos.
8 starsOPEN
04WIRELESS INTELLIGENCE
IEEE INFOCOM 2021 · Python · MATLAB
DyLoc
Predictive recurrent neural networks that localize moving users from massive-MIMO wireless channel sequences.
46 citationsOPEN
MORE OPEN-SOURCE WORK
02 / RESEARCHMAKING THE
MAKING THE
INVISIBLE
USEFUL.
My research applies learning to wireless signals: localization, massive MIMO, mmWave beam selection, radar, and spectrum intelligence.
GOOGLE SCHOLAR206TOTAL CITATIONS
8H-INDEX
17LISTED WORKS
0146 CITES0243 CITES0318 CITES
DyLoc: Dynamic Localization for Massive MIMO Using Predictive Recurrent Neural Networks
IEEE INFOCOM · 2021
PARAMOUNT: Generalizable Deep Learning for mmWave Beam Selection
IEEE Transactions on Wireless Communications · 2023
A CSI-Based Data-Driven Localization Framework Using Small-Scale Training Datasets
IEEE Transactions on Wireless Communications · 2024
03 / ABOUTRESEARCHER
RESEARCHER
TURNED BUILDER.
I work where machine learning, product engineering, and complex real-world systems meet.
My path runs from signal-processing research to production AI at Qualcomm, Adobe, and Snowflake. I care about ambitious technology, but I care more about making it understandable, dependable, and useful.
Outside my day job, I build and publish open-source tools that turn repetitive knowledge work into transparent human-in-the-loop systems.
2026 — NOWSNOWFLAKE
Staff AI/ML Engineer
2024 — 2026ADOBE
Staff ML/AI Engineer
2021 — 2024QUALCOMM
Senior ML Engineer
2019 — 2021UCF
Postdoctoral Research Scientist