Vetted OCR Professionals

Ruojie Hao

Screened

Mid-level Full-Stack Engineer specializing in AI, real-time web apps, and 3D/GIS systems

Seattle, WA6y exp

“Frontend-focused engineer who built and fully owns an interactive portfolio site showcasing real-time and 3D browser experiences, including WebGPU and WebSocket integrations. Stands out for combining polished UI design with deep browser-performance work such as progressive loading, GPU buffer batching, and React render optimization.”

“Built and productionized LLM-powered workflows that generate contextual insights from structured financial data, including prompt/retrieval design, data standardization, and reliability controls like rate limiting and batching. Also diagnosed and fixed real-time failures in an automated order validation system using logs/metrics, staging reproduction, edge-case handling, retries, and alerting, while supporting sales/customer teams with demos, scripts, and FAQs to drive adoption.”

“Manual QA tester with ~3 years of experience and a strong gamer/end-user mindset, aiming to transition into console game testing. Has provided UX-focused feedback to product leadership and prefers a collaborative, less-structured workflow (e.g., live testing with engineers in local environments to reduce downstream defects). Not yet familiar with console certification standards (TRC/XR/LOT) but highly motivated to learn.”

Haneesh Kapa

Screened

Junior AI Full-Stack Engineer specializing in LLM automations and RAG systems

Nashua, NH2y exp

“Built and shipped a production LLM-powered customer support assistant using a Python/FastAPI backend with RAG (embeddings + vector search) over internal docs and product/operational data. Instrumented the system with logging/metrics and ran continuous eval loops; post-launch improvements focused on retrieval quality (chunking/ranking) and performance/cost tradeoffs (query classification, caching, validation guardrails).”

“Built a university campus assistant chatbot (BabyJ/WWJ) using RAG and agentic routing with a FastAPI + React stack and JWT auth, focusing heavily on production concerns like latency and reliability. Uses techniques like speculative prefetching, smart intent routing, and rigorous eval/testing (golden sets, regression, edge cases) while collaborating closely with campus admin/advising teams to iterate based on real user feedback.”

“Full-stack AI engineer who has built and deployed multiple end-to-end LLM products, including an AI interview assistant, a multi-agent market research platform, and a policy document explainer. Particularly strong in productionizing agentic workflows, integrating tools like Whisper, Tavus, LiveKit, CrewAI, and LangGraph, and hardening messy real-world AI/document pipelines with validation, memory isolation, and fallback handling.”

Abhay Bisht

Screened

Junior Software Engineer specializing in AI-powered full-stack SaaS

Bangalore, India2y exp

“AI-first developer who reports using agents for roughly 85% of coding work, with a disciplined process centered on detailed specs, prompt design, review, and testing. Has built a personal multi-agent orchestration setup with specialized agents for testing, PR extraction, review, and synthesis, and stays current through AI engineering newsletters and a network of AI companies.”

“Project lead who restored a 1999 vintage museum robotics exhibit by inventorying and integrating legacy systems, reverse engineering original behavior, and reimplementing it in a modern codebase. Notably optimized Tesseract OCR and machine-vision pipelines to run on a 400MHz Pentium III with 256MB RAM while bringing up and tuning degraded FireWire IIDC cameras using scarce legacy documentation.”

Muhammad Murtaza Murtaza

Screened

Mid-level Machine Learning Engineer specializing in NLP, Computer Vision & Predictive Analytics

Islamabad, Pakistan5y exp

“Built a production LLM fine-tuning pipeline for domain-specific code generation at Pigeonbyte Technologies, including automated collection and rigorous quality filtering of 10M+ code samples (AST validation, sandbox execution/testing, deduplication, drift monitoring, and human-in-the-loop review). Also implemented end-to-end ML orchestration in Apache Airflow with data quality gates, dataset versioning in S3, benchmarking, and automated model promotion, and has a reliability-first approach to agent/workflow design.”