Vetted Database Design Professionals

Dhairya Shah

Screened

Entry-level Machine Learning Engineer specializing in computer vision and systems

Buffalo, NY1y exp

“ML-focused builder who has shipped an end-to-end income-class prediction product: built the data pipeline, trained models, deployed via Streamlit with a live UI, and tracked success via accuracy (84%), adoption, and latency. Demonstrates strong practical MLOps instincts (Docker/Streamlit Cloud, logging/monitoring, caching) and data engineering reliability patterns (schema checks, idempotency, retries, backfills) while iterating quickly in ambiguous, solo-project environments.”

Iskhak Ishmakhametov

Screened

Mid-level Full-Stack Software Engineer specializing in FinTech and real-time systems

Bellevue, WA7y exp

“Full-stack product engineer with a strong real-time systems focus: built and rolled out a WebSocket-based notifications system (with robust reconnect/resync and event ordering protections) that cut update latency to under 200ms. Also owned a workflow automation platform backend in FastAPI (JWT/RBAC, versioned APIs, standardized errors), designed the PostgreSQL schema for workflows/tasks/executions, and operated deployments on AWS ECS Fargate with blue-green CI/CD and performance stabilization via caching and autoscaling.”

“Machine learning lab assistant at Eastern Illinois University who productionized a voice-enabled conversational AI system: redesigned it with RAG, LoRA fine-tuning (including text-to-SQL), and safety guardrails, then deployed a scalable API supporting ~1,000 daily queries. Also partnered with customer-facing teams during a BlueFi internship by building demos/APIs and accelerating releases via Terraform + AWS CI/CD automation.”

Venkata Bayarapuneni

Screened

Junior Full-Stack Developer specializing in JavaScript, Python, and cloud-deployed web apps

Remote, USA1y exp

“Built and deployed a production LLM-powered travel assistant (Globe Trote) that automates end-to-end trip planning using a multi-step agent pipeline with RAG, external API calls, and enforced structured JSON outputs. Focused on reliability (validation, retries, fallback prompts, logging) and reported a ~30–40% reduction in irrelevant/generic responses after adding retrieval grounding.”

“Builder with hands-on experience shipping full-stack products across AWS cloud infrastructure, React/TypeScript apps, SQL-backed systems, and privacy-focused AI workflows. Stands out for combining cost-aware architecture, strong debugging instincts, and product thinking—from an e-commerce platform automated with IaC to a university admin portal serving 10,000+ users and a locally run AI assistant with configurable guardrails.”

eman akram

Screened

Junior Full-Stack Developer specializing in AI/ML and mobile/web apps

Wah Cantt, Pakistan2y exp

“Built an end-to-end car maintenance application from design through deployment using TypeScript/React with a Node.js + Firebase backend, including OBD integration. Uses mock servers and a layered frontend architecture (UI/state/services separation) to iterate quickly on UX without being blocked by backend or hardware dependencies.”