Shubhankar
Tiwari
I build backend systems that hold in production — and evaluate whether AI ones will too.
Backend Engineering
Production Java microservices for enterprise fintech — designed, deployed, and kept alive under real load.
Production Reliability
Incident triage, CI/CD ownership, and release validation in high-availability distributed systems.
LLM Evaluation
Behavioral consistency research — measuring whether a model is trustworthy enough to deploy, not just whether it can get the right answer once.
ML Research
Kaggle Notebooks Expert, top 4.1% globally. Applied ML across NLP, CV, and regression — now focused on evaluation infrastructure.
My Journey
I went from curious undergrad to backend engineer at Bank of America. The path wasn't linear — four years of production systems, a Kaggle Expert rank, and now building evaluation infrastructure for LLMs. Each of those things informed the others more than I expected.
B.Tech CSE
SRM Institute of Science & Technology
Graduated with 94.4% GPA in Computer Science. Built foundation in algorithms, data structures, and software engineering.
Software Engineer
Bank of America
Building and maintaining Java backend systems for corporate banking. I own the full lifecycle — design, CI/CD, deployments, and being on-call when something breaks. Four years of that teaches you things about software that writing code in isolation doesn't.
Kaggle Expert
Top 4.1% Globally
Notebooks Expert ranked #2,441 / 59,663 — personal best #707. 34 notebooks and 10 bronze medals across ML, DL, NLP, Computer Vision, and regression.
Backend Excellence
Currently at Bank of America, I focus on building microservices that power critical banking workflows. From API design to deployment validation, I own the full lifecycle.
Competitive ML
Outside of work, I sharpen my skills through Kaggle — ranked top 4.1% globally, personal best #707. Currently researching LLM behavioral reliability and building evaluation infrastructure that measures production-readiness, not just benchmark accuracy.
Engineering at Scale
At Bank of America I work on backend systems that process real financial transactions. My job isn't just writing code — it's release validation, production triage, and being accountable when a deployment goes wrong at an inconvenient hour.
I've been doing this for four years. The thing that changes is your relationship with failure. You stop being surprised by it and start building systems that tell you clearly when and why they're failing.
Engineering Principles
Featured Work
Selected projects and experiments
Production-grade system for measuring LLM behavioral consistency via Monte Carlo sampling. Benchmarked Qwen 2.5-7B across 240 inference calls — v2 grid sweep found temperature IS a lever, but top-p dominates 3.1×.
End-to-end multilingual LLM training pipeline targeting Hindi/English code-switching. Dataset curation, LoRA fine-tuning, inference evaluation, and deployment packaging across 6 Kaggle notebooks.
ML-based workout song recommender using BPM and VADER sentiment analysis. Co-authored research with K-Means clustering on Billboard Top 100 to match songs to exercise intensity.
Notebooks Expert rank #2,441 / 59,663 — personal best #707. 34 notebooks, 11 datasets, 3 models, 1 competition entry. 10 bronze medals across ML, DL, NLP, Computer Vision, and regression.
Production quality-gating system for AI-generated outputs in financial services — threshold optimisation, conservative AND escalation policy, priority-scored human review queue, and audit-grade provenance.
Technical Arsenal
Backend Systems
Data & Persistence
Platform & DevOps
ML & AI
Credentials
Kaggle Notebooks Expert
Rank 2,441 / 59,663 · 10 Bronze Medals
B.Tech CSE — SRM IST
94.4% GPA · 2018–2022
ML, Deep Learning, CV
Kaggle Certified · 2025
Interactive Terminal
Try: help, about, ls projects/, cat skills, neofetch
Get in touch
Open to roles in backend systems, platform engineering, and applied AI. If something here resonates — I'd like to hear from you.
tiwarishubhankar@gmail.com