Vetted A/B Testing Professionals

“Built and productionized a real-time social-media sentiment analysis system used by a marketing team to monitor brand/campaign performance. Experienced in orchestrating LLM workflows with LangChain (validation → prompting → parsing → post-processing), plus monitoring, retraining, and RAG-style retrieval using embeddings/vector stores to keep outputs reliable over time.”

“UX/Product designer with agtech internship experience designing an end-to-end platform, including user journeys, interaction models, and a clean visual design system. Has hands-on field research experience on farms that directly shaped mobile-friendly UI decisions (one-handed, on-the-move workflows) and a front-end development background (React/HTML/CSS/JS) that supports smooth engineering handoff.”

“ML practitioner who built a production customer risk scoring system to replace slow manual approvals, owning the full pipeline from feature engineering and XGBoost training to deploying a Dockerized FastAPI prediction service. Emphasizes reliability and business-aligned evaluation (recall/ROC-AUC, threshold tuning, drift monitoring) and is comfortable translating model decisions into stakeholder metrics like conversion rate (experience at EasyBee AI).”

Lando Ringel

Screened

Senior Unity Developer specializing in AR/VR, AI, and game systems

Melbourne, FL11y exp

“Game developer with a distinctive niche in integrating LLM-driven dialogue directly into Unity gameplay, including a full web-hosted architecture using llama.cpp, FastAPI, and cloud GPUs for real-time NPC interaction. Also brings VR/mobile optimization experience from a drone simulation project at GovScio, combining AI systems thinking with practical 3D environment and performance work.”

“Early-career product designer with strong end-to-end ownership on a thesis product, Klaro—a smartwatch-led gym guidance experience for beginners focused on reducing hesitation and anxiety in the moment. Stands out for combining UX craft with scrappy product validation, including a 14% waitlist conversion test and a navigation experiment that helped users reach equipment about 40% faster.”

Yash Mahajan

Screened

Junior Software Engineer specializing in AI, full-stack development, and applied ML

Fullerton, CA2y exp

“AI/full-stack product builder who has shipped production agentic systems in both customer support analytics and medical claims automation. They combine React/Next.js frontends with Python-based async backends and LLM orchestration, delivering measurable outcomes like 60% cost savings, 40% less manual review, and reducing claims processing from 30 minutes to 20 seconds.”

Hamna Anwar

Screened

Senior Full-Stack Engineer specializing in Go backend systems

Hayward, CA8y exp

“Full-stack/backend engineer with startup-style experience spanning healthcare and B2B infrastructure SaaS. Has worked across Python, Go, and React/TypeScript, including migrating services from Node.js to Go, building microservices and dashboards, and delivering measurable API performance gains through database tuning and Redis caching.”

“Built and owned the core execution pipeline for Drona, an AI code grading platform, spanning Next.js frontend, real-time WebSocket updates, Celery/Redis async processing, Docker sandboxing, and PostgreSQL persistence. Particularly strong in backend reliability and architecture, with concrete wins including reducing API response time from about 5 seconds to 200 ms and eliminating silent job failures in production.”

“Growth/marketing operator with hands-on experience across creator partnerships and performance acquisition. Sourced creators via TikTok Creator Marketplace and qualitative engagement checks, negotiated performance-based deals, and achieved a 15% CPA improvement that expanded into a long-term ambassador program. Also led persona-based GTM and funnel experiments at Haletale, driving a 20% lift in demo bookings without increasing budget.”

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.”

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 and deployed a production RAG-based internal document Q&A system using LangChain, vector search, and a dockerized FastAPI LLM service. Focused on reliability by systematically reducing hallucinations and improving retrieval through prompt grounding/abstention strategies, chunking and top-k tuning, and iterative evaluation with logged metrics and manual validation.”

“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.”

“ML/NLP engineer who has built production systems end-to-end: a real-time recommendation platform (100k+ profiles) using BERTopic-style clustering and a RAG-based news summarization/recommendation stack with ChromaDB. Strong focus on scaling and reliability (GPU batching, Redis caching, Kafka ingestion, Docker/Kubernetes, Prometheus/Grafana) and on maintaining model quality over time via drift monitoring and retraining triggers.”

Amir Temtem

Screened

Junior Growth & B2B Marketer specializing in SaaS, EdTech, and revenue operations

Tunis, Tunisia2y exp

“Growth/partnerships-focused operator with experience in early-stage B2B GTM and creator/education-adjacent ecosystems. Helped increase brand credibility by bringing a psychiatrist on as a pedagogic consultant and launching a learning-disabilities podcast, contributing to 2 new B2B partnerships in a year and opening sponsorship opportunities; also uses LinkedIn warm outreach and cold outbound (email/calling) to reach decision makers.”

Puspa Oli

Screened

Junior Machine Learning Engineer specializing in NLP, Computer Vision, and FinTech AI

Kathmandu, Nepal2y exp

“AI/LLM engineer who has shipped production RAG and agentic systems end-to-end (LangChain/FAISS, OpenAI+Gemini, FastAPI, Docker, Streamlit), focusing on retrieval quality and low-latency performance. Also partnered with a non-technical PM at deepNow to deliver a forecasting + summarization pipeline for daily market insights with iterative prototyping and a simple UI.”

“Unity developer with strong real-time 3D and mobile performance optimization experience (rendering, memory, GC), building interactive environments and physics-based interactions. Built a mobile Unity game prototype largely solo end-to-end, emphasizing state-driven architecture and clean separation between game logic, UI, and data—skills that translate directly to AR/VR despite no shipped Meta Quest titles.”