Arsalan Shaik
I teach machines to be less annoying.
CS student at UT Dallas (graduating Dec 2026), most recently building LLM-powered automation at Staples and wrangling large-scale data pipelines at Intuit. I like the unglamorous parts of AI/ML — the inference layer, the pipeline that has to run at 3am, the prompt that has to hold up in production, not just in a notebook.
Resume
Work Experience
Software Engineer Intern
Staples
- Collaborated with the internal tools team to build an LLM-powered workflow automation system using GPT-4o, reducing manual operational overhead by ~15 hours/week.
- Designed and optimized the model inference layer, including context window management, system prompt architecture, and parameter tuning to meet production accuracy requirements.
- Integrated the LLM backend with internal systems via REST APIs, implementing structured output parsing, fallback handling, and response validation to ensure reliability at scale.
Data Engineer Intern
Intuit
- Contributed to a team-owned Apache Beam pipeline modeling user sessions from live event streams; personally developed a Python module to monitor Kafka consumer lag and surface scaling recommendations, reducing processing delays by ~30% during peak traffic.
- Implemented backward-compatible schema updates via Confluent Schema Registry across 10+ event types, ensuring zero-downtime changes for downstream consumers.
- Collaborated with the data engineering team to migrate 15+ on-premise processing jobs to AWS (S3, Redshift); wrote validation scripts to verify data integrity post-migration, improving average query performance by ~25%.
Projects
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Skills
Languages
Databases
Tools & Frameworks
ML & AI Frameworks
Libraries
Certifications
PCEP – Certified Entry-Level Python Programmer
Python Institute
Microsoft Certified: Azure Fundamentals
Microsoft
Microsoft Certified: Azure Data Fundamentals
Microsoft
Recent Events
HackUTD
HackathonNov 2025 · Richardson, TX
Location Discovery Platform
At UT Dallas's flagship 24-hour hackathon, built a location-discovery platform with a team of four that scrapes TikTok and Instagram for trending places, uses AI to interpret natural-language search and generate location descriptions, and runs geospatial search over PostgreSQL/PostGIS.
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