class Jeet:
role = "Software Engineer | AI/ML Engineer"
degree = "M.S. Data Science Β· Indiana University Β· GPA 3.8/4.0"
location = "Bloomington, IN β Open to Relocation"
focus = [
"Production LLM systems & GPU inference optimization",
"High-throughput backend services with AI/ML integration",
"Distributed data pipelines & MLOps at scale",
"Reliable, observable, maintainable software",
]
currently_building = "LLM inference APIs + backend systems that work in prod, not just notebooks"| π | Metric |
|---|---|
| 14M+ | Nonprofit records served in production |
| 1,600Γ | Latency reduction via Redis caching (8.3s β 5ms) |
| 180ms | P50 inference latency on GPU-backed LLM service |
| 500K+ | Creatorβbrand interactions on AI-powered platform |
| 0.95 | RΒ² on Medicare billing prediction pipeline |
| 78 | Latent funding networks discovered via Neo4j |
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π I Built a Subscription Backend Like Stripe in 6 Hours β Here's What I Learned
I'm open to full-time roles in software engineering, AI/ML engineering, and backend systems.
jeetp5118@gmail.com Β· LinkedIn Β· Portfolio Β· Medium
