Vetted HTML Professionals

“Built a voice-driven desktop assistant for users with mobility impairments, integrating Whisper and Google Gemini and adding voice-authentication via speaker embeddings for secure command execution. Has hands-on experience with AWS serverless/microservices patterns (Lambda, S3, CloudFront, CloudWatch) and CI/CD, plus built an internal MySQL-to-MongoDB migration tool used by the CTO and dev team with an emphasis on safe, low-impact data transformation.”

“Application-focused engineer who has shipped end-to-end products across mobile and web, including a music-based dating app feature for sending searchable/previewable songs in chat and a geospatial events service integrating external APIs. Demonstrates strong product + engineering instincts: performance-minded PostgreSQL modeling, Dockerized deployments with env-based config, and UX/accessibility polish backed by user studies, plus hands-on incident mitigation using Vercel logs.”

“Python/Django backend engineer with open-source experience upgrading Archivematica to Django 4.2 LTS, including resolving a tricky breaking change in datetime parsing by implementing a preservation-safe legacy timestamp conversion layer. Also built a cost-efficient, reproducible Small Language Model (Microsoft Phi-3) fine-tuning pipeline that turns CSV product data into a domain-specific searchable Q&A chatbot, with emphasis on memory optimization and overfitting prevention.”

“Full-stack system analyst/programmer at PeakPlay Sports (startup) who built an AI "coach" product end-to-end in ~2 months, using a LangGraph-orchestrated multi-agent architecture with a FastAPI backend. Shipped production RAG grounded in athlete history (OpenAI embeddings + vector store) with guardrails and a structured eval loop (golden set + LLM-judge + human review) to improve engagement and reduce hallucinations.”

“Full-stack developer who owned and shipped an end-to-end web application for LeafNBeyond (React/Node/Postgres), deployed to production at leafnbeyond.com, with reported 35% sales growth and strong UX feedback. Also built Azure-based ETL pipelines using lakehouse/medallion architecture with validation and retry logic, and has AWS fundamentals from a master’s coursework (EC2, RDS, IAM, load balancing).”

“Robotics software contributor from Binghamton University’s drone research lab who built a Dockerized, multithreaded Python control stack integrating Crazyflie firmware for low-latency, real-time coordination of multiple drones. Hands-on with telemetry/command pipelines, profiling and control-loop optimization, and wireless comms using CrazyRadio PA.”

“Robotics software engineer with ROS 2 Humble/Nav2 experience on a warehouse robot fleet, focused on improving throughput in dynamic human environments. Implemented C++ local-planner and velocity-control changes using LiDAR-based motion prediction and real-time costmap tuning under a 20ms control loop, and built a Gazebo digital twin with custom failure-injection plugins plus Docker/Kubernetes deployment tooling.”

“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.”

“Frontend engineer focused on scalable React + TypeScript dashboards and workflows, using feature-based architecture and a reusable component/hook approach. Has hands-on experience improving performance in table-heavy admin UIs (pagination, lazy loading) and shipping major features quickly with staging/manual QA, gradual rollouts, and rapid iteration based on production feedback.”

“Software engineering intern who built and deployed a full-stack telemedicine platform (React/Node/MongoDB) used daily in a pediatric clinic, incorporating PyTorch-based predictive features. Demonstrated strong customer-facing iteration and production performance debugging—resolved a live slowdown by indexing/optimizing MongoDB queries and adding caching, improving response times by ~50%.”

“No prior professional console QA experience stated, but demonstrates detailed, end-to-end knowledge of multi-platform console testing and certification (TRC/XR/Lotcheck), including system event coverage, performance/soak testing, multiplayer/network scenarios, and certification-focused bug reporting. Proposes using AI to turn platform requirements into structured checklists/test cases and daily status summaries to reduce certification risk.”

“Aspiring Console QA candidate with hands-on PlayStation and Nintendo Switch testing instincts developed through deep gaming experience (edge-case inputs, handheld vs docked comparisons, online play smoothness). Has delivered under tight deadlines on a small-team project and has practical experience using internal AI tools to draft test documentation and analyze report/feedback data to identify patterns and prioritize issues.”

“Backend/ML engineer with healthcare domain experience building secure Medicare/Medicaid data APIs and real-time patient risk scoring. Shipped an end-to-end ML pipeline (scikit-learn/XGBoost) served via SageMaker and integrated into Flask APIs, with strong production reliability practices (Kafka schema validation, regression replay, observability, drift monitoring, and human-in-the-loop guardrails).”

“Full-stack engineer at Srasys Inc. who built and owned production payments/checkout for an e-learning platform serving 5,000+ users using Next.js App Router + TypeScript. Deep focus on correctness and reliability (Stripe webhooks, signature validation, DB-level idempotency) plus measurable performance wins (~40% latency reductions) through Postgres indexing/EXPLAIN ANALYZE and Redis-backed caching with CloudWatch monitoring.”

“Built and shipped production AI features in the automotive dealership domain, including an end-to-end computer-vision damage detection system for trade-ins and a tool-calling, RAG-enabled LotSync AI Agent that answers inventory/VIN questions using strict schemas and internal APIs to avoid hallucinations. Also developed a Dagster + Oracle automated reporting pipeline as a Graduate Research Assistant, supporting 15+ university departments with normalized, reliable ETL workflows.”

“Early-career/out-of-college CS candidate with practical backend-adjacent experience in a wine storage business: helped shift client intake from Constant Contact to a website form and supported an internal migration to Storable Edge with Dropbox-based backups. Also has academic experience debugging a custom programming language/type system, catching an edge case that broke type definitions and caused crashes.”

“UX Designer who has shipped end-to-end mobile and web experiences, including a student library companion app integrated with Canvas to reduce navigation friction and overwhelm. Also built information architecture and navigation for a bead e-commerce site (Beadalon) using Miro/WordPress/WooCommerce and validated improvements via analytics. Has experience designing a mental-health journaling companion with guided prompts and sketching based on student interviews and prototype testing.”

“Frontend engineer who led end-to-end delivery of a React/Next.js platform and real-time analytics dashboard at HacknoTech, emphasizing scalable UI architecture and performance. Uses a pragmatic state strategy (React Query for server state, Redux Toolkit for UI state), built shared component libraries with Tailwind, and improved load times by ~40% through code splitting/lazy loading and Lighthouse-driven tuning.”

“Internship-built full-stack systems spanning HR employee-record portals and internal data-quality dashboards (Flask + SQL + React), emphasizing data integrity and rapid MVP iteration. Also implemented Flask microservices with RabbitMQ for distributed task processing, addressing duplication/ordering issues with idempotency, durable queues, and correlation-ID logging; delivered quantified productivity gains for HR teams.”

“Frontend engineer who has led workflow-heavy React/TypeScript products end-to-end, emphasizing feature-based architecture, reusable UI patterns (forms/tables/async states/permissions), and performance optimization for data-dense dashboards. Strong track record of shipping quickly with quality via PR standards, targeted testing, UAT, staged rollouts, and iteration driven by analytics, error reports, and operator feedback.”

“Full-stack engineer (4+ years) with a Master’s in Computer Science who owned end-to-end customer-facing social networking features at NextBits, building TypeScript/React/Next.js + NestJS systems with microservices, RabbitMQ, MongoDB, and Redis. Experienced scaling real-time notifications/messaging/presence to millions of concurrent users with sub-100ms performance targets, zero-downtime CI/CD, and internal tooling for monitoring AI/ML pipelines and queue backlogs.”

“Master’s thesis focused on building and deploying a gait-based biometric authentication system using mobile accelerometer time-series data as an alternative to passwords/2FA. Emphasized real-world robustness by addressing sensor noise and variability (phone placement, walking speed, footwear) and improving safety using biometric metrics like FAR/FRR and EER, while collaborating closely with a non-ML thesis advisor.”

“Backend engineer at Hexanika who owned a real-time fraud-detection platform: built Django microservices, integrated a GenAI anomaly-scoring model, and optimized data/infra for low-latency production (including ~40% query-latency reduction). Experienced running containerized services on AWS/GCP with Kubernetes/GKE, GitHub Actions-based CI/CD + GitOps, and building Pub/Sub streaming pipelines and on-prem-to-cloud migrations.”

“Worked on an AI-adjacent search/results product with a React front end and an API-driven backend, focusing on scalability and performance. Emphasizes decoupled JSON API architecture, React rendering optimizations (useMemo/useCallback), and large-dataset techniques like virtualization, plus strong user-issue triage via log analysis and edge-case fixes in query handling/ranking.”