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name: Yash Shah
location: Seattle, WA 🌧️ (originally from India ☀️)
education:
- degree: "M.S. Computer Software Engineering"
university: "Arizona State University"
gpa: 4.0 / 4.0
minor: "Data Science"
duration: "Aug 2024 – May 2026"
- degree: "B.Tech Computer Science & Engineering"
university: "Charotar University of Science and Technology"
gpa: 9.54 / 10
duration: "Aug 2020 – May 2024"
currently:
- "🔬 Researching distributed systems & ML pipelines"
- "⚡ Building high-throughput, fault-tolerant backend systems"
- "📖 Always reading papers on LLMs and Systems design"
fun_facts:
- "I reduced AWS Lambda fleet load spikes by 60% 🚀"
- "Published in IEEE Xplore"
- "I think in terms of latency, throughput & fault tolerance"🟠 Amazon Web Services · SDE Intern · Seattle, WA · May–Aug 2025
Working deep inside AWS Lambda's core infrastructure — the service that handles trillions of function invocations.
- ⚡ Engineered improvements to Lambda's Proactive Spin Up (PSU) system, slashing Top-of-the-Hour fleet load spikes by 60%
- 📊 Built CloudWatch observability pipelines and dashboards to monitor fleet health across distributed serverless infrastructure
- 🔄 Engineered data transformation and model pipelines to optimize flow between system inputs/outputs across Lambda's distributed architecture
- 🛠️ Contributed to on-call readiness by debugging production issues in distributed Lambda infrastructure
🔵 Kintu Designs · ML Intern · India · Jan–Apr 2024
Built an NLP-powered platform to analyze student feedback at scale.
- 🗣️ Processed 10,000+ feedback submissions, cutting manual review time by 40%
- 🤖 Trained Logistic Regression & Decision Tree classifiers with NLP preprocessing (tokenization, lemmatization)
- 🎯 Achieved 85%+ sentiment classification accuracy and surfaced top themes per course cohort
🟣 Brainy Beams Technologies · Data Science Intern · India · Jun–Sep 2023
End-to-end ML pipeline for diamond price prediction.
- 💎 Built full EDA → feature engineering → ensemble model pipeline achieving R² = 0.92
- ⬆️ Improved prediction accuracy by 15% on held-out test data
- 🗄️ Optimized MySQL/PostgreSQL queries with indexing, cutting execution time by 30% and enabling 3× faster ML data ingestion
High-throughput BLE telemetry + fault-tolerant data pipeline
📡 10,000+ battery readings/day · 📉 35% overhead reduction
🔌 Offline-first SQLite queuing · 🔒 SHA-256 OTA firmware delivery
Transfer learning for real-world video security systems
🧠 Models Evaluated: DenseNet121, VGG16, VGG19, ResNet50
🏆 Best: DenseNet121 → ROC-AUC: 0.85
🛠️ Stack: TensorFlow · Keras · PyTorch · UCF Crime Dataset
{
"languages": ["Python", "TypeScript", "Java", "Go", "Rust", "C", "C++", "JavaScript"],
"frontend": ["React.js", "Next.js", "React Native", "HTML/CSS"],
"backend": ["Node.js", "Express.js", "FastAPI"],
"databases": ["PostgreSQL", "MySQL", "MongoDB", "DynamoDB", "Redis", "Firebase"],
"cloud": ["AWS Lambda", "SageMaker", "EC2", "RDS", "GCP"],
"devops": ["Docker", "Kubernetes", "Jenkins", "Kafka", "CI/CD", "Git"],
"systems": ["Distributed Systems", "Load Balancing", "Caching", "CDN",
"Fault Tolerance", "High Availability", "Linux/Unix"]
}| Channel | Link |
|---|---|
| shahyash452@gmail.com | |
| linkedin.com/in/shahyash452 | |
| 🌐 Portfolio | yashshah.vercel.app |
| 📝 Medium | @shahyash452 |
| 📞 Phone | (602)-328-6795 |
╔══════════════════════════════════════════════════════════╗
║ "The best systems are invisible — until they break." ║
║ — Yash Shah ║
╚══════════════════════════════════════════════════════════╝
Built with obsession over distributed systems, clean abstractions, and coffee ☕