Software Engineer · Finaptive · prev. AMD
Engineering systems that hold up under real-world constraints.
I'm Yash Bhavsar — a software engineer at Finaptive building production financial platforms, previously at AMD. I work across applied ML, financial-data pipelines, and developer tooling, with a bias toward clean architecture and tests that actually mean something.
01 — Selected Work
Things I've built
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01
Instaply
GitHubA job-discovery engine that monitors ATS feeds and ranks roles against your résumé — entirely on your machine.
- Hybrid match scoring — 60% deterministic + 40% LLM judge over local sentence-transformer embeddings; your résumé never leaves the device.
- Ingests Greenhouse, Lever & Ashby feeds with budget-aware Gemini scheduling and graceful fallback when the quota runs out.
- 74 modules, 40+ tests, SQLite embedding cache, scheduled digest emails.
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02
Asterion
GitHubA moving-object detection pipeline that finds asteroids in real telescope imagery.
- 100% recovery completeness for SNR ≳ 11 with zero false positives on injection–recovery benchmarks.
- Pulls real ZTF survey frames from IRSA and cross-matches detections against SkyBoT to name known asteroids.
- 5–7 Mpix/s on a laptop; 43 unit/integration/API tests; no-build SPA served over FastAPI.
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03
Stride
GitHubAn equity screener that surfaces stocks turning from selling exhaustion into early institutional accumulation.
- Deterministic four-stage funnel: Technical Setup → Hype Filter → Fundamental Floor → Smart-Money Confirmation.
- Blends yfinance, Finnhub, SEC EDGAR & Reddit signals; every threshold is config-driven so output is fully reproducible.
- 53 modules, Typer CLI + FastAPI, structured logging, 15+ tests.
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04
Code Atlas
GitHub“Google Maps” for a codebase — turns a repo's full history into an explorable knowledge graph.
- Ingests files, symbols, dependencies, commits & PRs into a graph with ownership, knowledge-concentration (Herfindahl) and risk lenses.
- Estimates AI-vs-human contribution and recommends the right reviewer for a change.
- React + Cytoscape front end over a FastAPI / PostgreSQL backend, fully Dockerized.
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05
Trading Engine
GitHubAn event-driven algorithmic-trading engine where the risk gate has the final say.
- A risk gatekeeper sits as a hard gate in front of every order — no strategy can bypass it.
- Event-bus architecture prevents look-ahead bias; the paper broker simulates slippage & commissions.
- 34 modules across 8 layers; backtest harness with drawdown / position metrics; YAML-configured.
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06
Lunar Landing RL Hackathon 🏆 1st place
GitHubA reinforcement-learning agent that took first place at an RL hackathon by learning to land the LunarLander.
- Deep Q-Network in PyTorch reaching a 285.3 reward score.
- Finished 1st out of 50+ competing teams.
Also built
- Intelligent Email Sorting ML pipeline (spaCy + NLTK) hitting 90% classification accuracy with GDPR-aware processing.
- Embedded LiDAR Mapping Low-level I2C/UART sensor integration with a Python 3D point-cloud visualizer.
- PseudoGate AST-based tool that injects AI-generated imperative logic into Python stubs.
- Crucible RL study — a PPO agent (~285 reward) benchmarked against four algorithms on LunarLander-v3.
02 — About
Who's building this
I like hard, well-defined problems — systems with real constraints, where correctness and architecture genuinely matter. At Finaptive I build production financial platforms; before that I was at AMD.
Most of what I build leans the same way: deterministic pipelines, applied ML and LLMs used with judgment rather than for show, and tools that make complex systems legible. I care about tests, clean boundaries, and shipping things that hold up after the demo.
B.S. Electrical Engineering — McMaster University.
- Languages
- Python · TypeScript · SQL · Java
- Backend
- FastAPI · Flask · Node.js · REST
- Data
- PostgreSQL · SQLite · MongoDB · Redis · Pandas
- ML / AI
- PyTorch · sentence-transformers · spaCy · LLM integration
- Infra
- Docker · Azure · GitHub Actions · CI/CD
03 — Contact