Faizan
Open to AI/ML engineering & research roles

About

I'm Muhammad Faizan Raza, an AI/ML engineer and researcher building real-time LLM systems that hold up in production: fast, current, and reliable under load.

Muhammad Faizan Raza

I build production LLM systems and study the methods that make them dependable. Most recently I was an AI/ML Software Engineering Intern at Zscaler, where I architected and shipped an LLM-powered MCP automation system that cut runtime 10× and drove ~$1M+ in annual savings across a 500B+/day events environment.

In parallel, as a Graduate Research Assistant at Penn State, I work on applied ML, NLP, and agentic AI over multi-million-record datasets, and publish on real-time, enterprise-ready LLM deployment. Before grad school I led data and analytics work at Beam AI (Berlin) and Daraz, building recommendation systems, ROI models, and operations analytics at scale.

I hold an M.S. in Data Analytics from Penn State (4.0 GPA) and a B.S. in Mathematics and Economics from LUMS. At Penn State I was named a Fox Scholar and Warren V. Musser Fellow and received the Outstanding Student Achievement Award. The through-line across it all is a systems mindset applied to machine learning: I care about the engineering that turns a capable model into a reliable, real-time system: latency budgets, freshness, cost, and safety.

Outside of work I'm drawn to startup ideation and open source, and I do design work rooted in my community, including event banner typography in Urdu and Arabic script.

Experience

Roles & impact

  1. May 2025 – Aug 2025

    Zscaler

    AI/ML Software Engineering Intern · San Jose, CA

    • Architected and productionized an LLM-powered Model Context Protocol (MCP) automation system orchestrating Hadoop→DBT migrations and pipeline deduplication across large-scale data infrastructure, at 95%+ task accuracy.
    • Shipped end-to-end with LangGraph, Redis, Postgres, and AWS: 10× faster runtime, ~70% lower latency, and ~$1M+ annual engineering cost savings across 100+ weekly workflows in a 500B+/day events environment.
    MCP LangGraph Redis Postgres AWS
  2. Sep 2024 – May 2026

    Pennsylvania State University

    Graduate Research Assistant, Data Science · Malvern, PA

    • Led end-to-end development of applied ML, NLP, and agentic AI systems over 10M+ record, multi-source datasets.
    • Built and deployed NLP pipelines (scraping, embeddings, supervised ML) over 1M+ text records at ~85–90% classification accuracy across energy, healthcare, and security domains.
    • Developed predictive and causal models, improving accuracy ~19% through feature engineering, PCA, and rigorous experimentation.
    Python NLP PyTorch Causal ML
  3. Feb 2023 – Aug 2024

    Beam AI

    Data Analytics Team Lead (GTM) · Berlin, Germany

    • Built production reporting pipelines and executive dashboards (Python, SQL, ETL), cutting reporting turnaround by 40%.
    • Engineered a recommendation system (collaborative filtering, Scikit-learn), improving precision 30% and product conversions 12%.
    • Developed predictive ROI models (Pandas, NumPy) supporting 5 enterprise PoCs (~€150K total contract value).
    Python SQL Scikit-learn ETL
  4. Jan 2021 – Dec 2022

    Daraz

    Data Analyst, Operational Excellence · Lahore, Pakistan

    • Led operations analytics across 50+ First Mile logistics stations, analyzing 1M+ customer-feedback records (SQL, Python) to surface systemic bottlenecks and drive an 18% increase in nationwide customer satisfaction.
    SQL Python Analytics

Featured in

Press & features

Toolkit

Skills

Languages

Python SQL JavaScript C++ R Linux

ML & AI

PyTorch TensorFlow Scikit-learn LangChain / LangGraph Hugging Face RAG Agentic AI NLP MCP vLLMs MLOps

Data & Infra

PySpark Kafka Airflow DBT Redis Snowflake PostgreSQL AWS GCP Azure Docker CI/CD

Analytics & Viz

Pandas NumPy Tableau PostHog