Vetted Data Visualization Professionals

Fatemeh Taghvaei

Screened

Junior AI/ML Engineer and Instructor specializing in deep learning, computer vision, and NLP

Chicago, IL2y exp

“Computer-vision practitioner and educator who built a real-time license plate recognition system (OpenCV/Python + KNN) optimized to run on a Raspberry Pi with camera integration. Also designs hands-on deep learning coursework, incorporating recent transformer-based vision research (Vision Transformers) into practical labs on real datasets.”

Husayn El Sharif

Screened

Senior Data Scientist specializing in geospatial ML and environmental analytics

Atlanta, GA16y exp

“Applied ML practitioner who deployed a near-real-time water-quality monitoring tool for Gwinnett County by fusing ESA satellite imagery with in-situ measurements to predict chlorophyll-A and support early warnings for harmful algal blooms. Also working on a multimodal deep-learning project combining skin lesion images with patient tabular/text data (TensorFlow, embeddings) to predict melanoma risk.”

Surya Vamshi Sriperambudooru

Screened

Mid-level AI Engineer specializing in healthcare claims analytics and RAG copilots

Remote, US4y exp

“Built a production "appeals co-pilot" for a healthcare claims appeals team, combining an XGBoost/logistic ranking model with a Python/LangChain RAG stack (FAISS + Mistral 7B) to surface high-probability appeal wins and speed policy-grounded drafting. Emphasizes reliability and trust: hybrid retrieval with metadata routing, citation/eval scripts, guardrails, and an explainability layer that non-technical stakeholders could understand and override.”

“Backend engineer who built an AI-driven "Smart Feedback Analyzer" API (Flask → FastAPI) that processes user feedback with NLP (Hugging Face + OpenAI) and returns structured insights. Demonstrates strong production-minded architecture: stateless services, Cloud Run + Docker deployment, Redis/Celery background processing, and Postgres/SQLAlchemy performance tuning (EXPLAIN ANALYZE, indexing, N+1 fixes), plus multi-tenant data isolation via JWT/API-key derived tenant IDs.”

“Full-stack engineer with hands-on production experience building real-time customer-facing features (order tracking + push notifications) across React/React Native and Node/Spring Boot with Postgres/MySQL. Demonstrates strong reliability patterns (transactional outbox, background workers, idempotent webhook ingestion) and has deployed/operated systems on AWS (ECS/Fargate/ALB, CloudWatch, CodePipeline) with structured observability and environment separation.”

Harikiran Jangam

Screened

Mid-level AI/ML Engineer specializing in NLP, LLMs, and RAG systems

California, USA3y exp

“Backend engineer who built and evolved a PHI-compliant RAG system (FastAPI + LangChain + embeddings/FAISS) for internal document search and summarization, delivering <400ms p95 latency at ~2,500 daily requests and measurable impact (30% faster investigations, +17% retrieval relevance). Demonstrates strong security and rollout discipline (RBAC/RLS/JWT, redaction/audits, shadow mode, dual writes, canaries) and a focus on reducing hallucination risk via grounded guardrails and confidence-based fallbacks.”

“Lifecycle/CRM marketer with hands-on experience building and QAing high-volume split-test campaigns in Salesforce and Braze. They emphasize experimentation and revenue impact, using Tableau-based KPI analysis (AOV, conversion, refund rate) to identify winners and scale successful tactics like interactive spinning-wheel offers across products.”

“Recent college graduate with early outbound experience as a student caller, where they stood out as a top performer by raising the highest donation amounts on many shifts. Their edge is a highly personal, relationship-first approach—moving beyond scripts to connect alumni memories and motivations to a compelling ask.”

“Full-stack JavaScript engineer (React/Node/Vue) who has operated like a maintainer by owning an internal component library with Storybook-style examples, documentation, and non-breaking versioning. Demonstrated strong performance engineering on a source code review service—profiling bottlenecks, fixing N+1 queries, adding caching, and trimming payloads to cut latency (e.g., ~100ms to <50ms) while rolling out incremental, test-backed improvements.”

Meet Vyas

Screened

Mid-level Software Engineer specializing in full-stack systems and AI applications

Tempe, AZ3y exp

“Software engineer with 3 years at Gap Inc. who led a major modernization from monolith/legacy frontend to a React and Spring Boot microservices architecture, delivering 25% cost savings, 30% faster releases, and 50% performance gains. Also built a 0→1 startup product, MealShare AI, using managed cloud services to rapidly launch a real-time food redistribution platform.”

“Built and significantly owned enterprise project-finance dashboards at Publicis Sapient, with a strong focus on performance, data freshness, and trust for demanding finance users. Stands out for diagnosing problems across both the browser and data layers—optimizing SQL, reducing DOM load, and redesigning interactions so users stopped exporting to spreadsheets and worked directly in the live dashboard.”

“Built and shipped enterprise AI products including a conversational SQL analytics platform and a production RAG system at Johnson & Johnson. Combines full-stack engineering with LLM systems expertise, and has delivered measurable impact at scale, including 48% lower retrieval latency and 37% better response relevance across 12M+ records.”

“Full-stack engineer who has owned an operations/reporting dashboard end-to-end, spanning React/TypeScript frontend architecture, ASP.NET Core APIs, and SQL data access. Stands out for combining strong UI performance optimization with pragmatic backend decisions, post-launch monitoring, and 0→1 startup platform building that improved API speed by 35% while supporting 2,000+ transactions per hour.”

Indra Shakya

Screened

Senior Full-Stack Engineer specializing in FinTech

Charlotte, NC8y exp

“Frontend-leaning full-stack engineer with deep experience building real-time financial trading platforms at Bank of America. They led modernization of a global markets product by consolidating three legacy apps into a single React/Next.js platform, built WebSocket-driven market data experiences, and helped drive shared component libraries and engineering standards used across multiple teams.”

“Data and backend-focused engineer with hands-on experience spanning GenAI applications, production telemetry systems, and large-scale ETL pipelines. They combine modern AI stack work (React, FastAPI, LangChain, ChromaDB) with measurable production impact, including 90% lower DB insertion latency, 50% higher ETL throughput, and 99.9% data quality in distributed environments.”

Saipraneeth Ketireddi

Screened

Mid-level AI/ML Engineer specializing in LLM automation and healthcare analytics

Dallas, TX4y exp

“Full-stack AI engineer who has repeatedly taken ambiguous automation and agentic products from prototype to production, including a BRD automation platform that cut manual processing by 70% and a healthcare RAG assistant with long-term memory. Stands out for combining backend/AI orchestration depth with strong product instincts around trust, observability, security, and non-technical user experience.”

“Frontend-focused engineer who built an expense management solution inside Microsoft Teams using React and Formily, modernizing reimbursement workflows that handle ~20,000 approvals per year. Demonstrated practical debugging and reliability improvements (stabilized multi-attachment uploads via event-binding investigation and hash-map-based targeting) and delivered ~30% performance gains by changing data structures, while coordinating stakeholders and team resources during quarter-end pressure.”

Nehemiah Dias

Screened

Senior Frontend Engineer specializing in design systems and real-time SaaS platforms

San Francisco, CA11y exp

“Full-stack product builder who has repeatedly taken end-to-end ownership in startup environments, including building PromoFlow solo and architecting the entire software backbone for Hard Drive. Particularly strong at turning ambiguous product needs into scalable systems, from real-time Firebase apps to shared component libraries and redesigned Postgres architectures, while also bridging non-technical founders, design, and engineering.”