Computer science student · deep learning researcher
I am Kunj Shah &
I am an average Deep Learning Enjoyer.
I’m Kunj, a computer science student focused on deep learning research. Working on all kinds of deep learning models. I explore how language and multimodal models learn, adapt, and behave through careful experiments and open work.
Experience & Education
Chronology of professional internships and academic coursework.
May 2026 — August 2026
A10 Networks
San Jose, CA
Deep Learning Engineer Intern — AI Firewall Team
- Architected and trained TrooperViz, a multimodal safety guardrail model built with Python, PyTorch, and Hugging Face Transformers, enabling comprehensive evaluation of text, image-text inputs, multi-turn conversations, and assistant-generated outputs across diverse safety categories.
- Fine-tuned a vision-language model for multimodal safety classification and merged it with a text-only guardrail model using SLERP, creating a unified safety system with broader coverage across visual, conversational, and generative-AI interactions.
- Engineered end-to-end data and evaluation workflows—including annotation, Pandas-based preprocessing, synthetic multi-turn conversation generation, model benchmarking, and interactive inference via Gradio and vLLM—streamlining the testing pipeline and accelerating safety assessments.
Python · PyTorch · SFT · SLERP · vLLM · Hugging Face · W&B · CI/CD
Oct 2025 — Apr 2026
Routes Technologies
Remote, TX
AI Engineer Intern
- Architected an LLM-powered NL-to-SQL RAG pipeline with few-shot prompting, input normalization (470+ synonym mappings), parameterized SQL sanitization, session memory, and Weights & Biases observability—deployed across 5 Azure ML managed online endpoints.
- Built an SVD collaborative-filtering recommendation pipeline on Azure ML, evaluated with precision, recall, and MAP metrics, and paired it with an LLM-driven taste profiler that batch-generates user preference vectors in a nightly ETL job, resulting in more relevant recommendations and faster cold-start handling.
- Engineered a multi-source recipe ingestion system using a Scrapy crawler with JSON-LD extraction, Instagram Graph API and TikTok oEmbed integrations, GPT-4o-mini for recipe classification, lingua for language filtering, and faster-whisper for audio transcription fallback, which expanded the recipe catalog and cut ingestion latency.
Python · SQL · Azure ML · scikit-learn · Sentence-Transformers · W&B · Scrapy
May 2025 — Aug 2025
Dreamable Inc.
San Francisco, CA
AI/ML Engineering Intern
- Trained, tuned, and deployed ML models in a production Cloud environment using Python, PyTorch, TensorFlow, and Hugging Face, working collaboratively with a cross-functional team.
- Fine-tuned Qwen-2.5-7B via LoRA on GCP Cloud to lower training cost while delivering a Q&A model with comparable accuracy within budget, tracking experiments with Weights & Biases.
- Curated NLP datasets (Pandas, NumPy, Hugging Face Datasets) to improve training data quality, and built a generative-AI outreach agent with LangChain and the OpenAI API to automate messaging workflows and increase response rates.
Python · PyTorch · TensorFlow · Hugging Face · LoRA · GCP · LangChain · W&B
Education
San Jose State University
2026 — 2027B.S. Computer Science · GPA 3.88
- NSP research with Professor William
- CodePath Advanced DSA training
- Dean's List Honoree
San Francisco State University
2023 — 2025Computer Science (Transferred)
- VP of AI Club & Tech Lead at SparkSF
- Hosted SFHacks (400+ attendees)
- Dean's List Honoree
Projects & Models
Pre-trained models, adapters, and open-source repositories.
Repositories
LLM Firewall for Agentic Tool-Calling
Low-latency inline defense intercepting prompt injections. GPT-2 attacker loop reduced bypass from 23.1% → 3.72%. BERT + LoRA adds ~20ms latency.
GitHubtheHelper — AI Research Assistant
Production RAG with FAISS, LangChain chunking, cross-encoder reranking. Local observability into daily JSONL. CI-gated QA.
GitHubKanting — Video RAG System
Indexes YouTube transcripts via Whisper. Semantic search across Sentence-Transformers DB returning precise clip timestamps.
GitHubHugging Face Weights
Qwen2.5-0.5B SFT+DPO 0.5B
Chat model fine-tuned with SFT and Direct Preference Optimization.
HuggingFaceSkills & Credentials
Technical expertise, hackathons, and certifications.
LLM Engineering
Transformers · SFT · DPO · GRPO · PPO · LoRA/PEFT · TRL · vLLM · Quantization · Vector DBs · Prompt Eng.
ML & NLP
PyTorch · TensorFlow · Scikit-learn · LangChain · FAISS · Whisper · BART · Sentence Transformers · Pandas · NumPy
Backend & Cloud
FastAPI · Flask · Docker · Azure ML · GCP · PostgreSQL · MongoDB · Scrapy · Nginx · CI/CD
Programming
Python · SQL · Java · JavaScript · C++ · Bash · R · HTML/CSS · Git · Linux
Hackathons
Certificates
- AI Memory: LLM Memory Systems — LinkedIn
- Fine-Tuning for LLMs: Beginner to Advanced — LinkedIn
- Model Context Protocol (MCP) — LinkedIn
- Introduction to Generative AI — Google Cloud
- Introduction to Web Development — UC Davis
- Programming in Python — University of Michigan
- Special Theory of Relativity — Stanford University
- Calculus through Data & Modelling (×4) — Johns Hopkins
Hobbies
What I explore outside of deep learning.
Astrophotography
I photograph planets, star clusters, galaxies, and nebulae using long exposures and image stacking.
View my astrophotography collectionGet in Touch
Send a brief message to open collaboration.
Open to inquiries about custom fine-tuning runs, alignment evaluation, and model safety audits.
Direct
kunjcr2@gmail.com