Vetted A/B Testing Professionals

“Full-stack engineer with a strong mix of real-time product engineering and applied AI experience. Built and deployed a production stock trading simulator on AWS and an LLM-based customer support agent with RAG/tooling, and also shipped a zero-to-one in-store detection feature at Meituan that improved CTR by 7% and conversion by 11%.”

Bharti Prasad

Screened

Executive growth and marketing leader specializing in consumer internet and gaming

Austin, TX15y exp

“Growth and GTM leader with end-to-end P&L ownership across e-commerce and real-money gaming, including scaling a fantasy sports product to the #4 player in its category and managing a 10M-user business. Particularly notable for launching a Tongits app in the Philippines remotely from India using self-directed market research, then doubling retention in 3 months and scaling it to #5 in the country.”

Vasudha Swaminathan

Screened

Executive product leader specializing in Enterprise SaaS and AI-powered platforms

Seattle, WA19y exp

“Product leader who helped build Stack Overflow for Teams from an unproven internal knowledge product into a $50M ARR business, later leading product, design, research, support, and analytics. Brings a distinctive point of view on human-centered AI from both Overflow AI and Sumble, with repeated evidence of pairing deep user discovery with measurable business outcomes like 20% conversion gains and sustained 100%+ NRR through strategic pivots.”

“Marketing designer/creative lead who builds scalable Figma-based systems for high-volume growth and community creative. Led a Recurly campaign aligned to a brand refresh (including creative testing like light vs dark), and served as the sole designer for Grow Therapy’s inaugural “Grow Forward” summit producing a full suite of event assets plus modular community templates for ongoing programming.”

Andrew Liang

Screened

Intern Software Engineer specializing in full-stack and AI/ML systems

2y exp

“Software engineer with experience at Amazon and Agora building end-to-end systems: a knowledge-base AI chatbot (React/TypeScript UI + retrieval/response backend + Docker deployment) and an internal approval governance platform using AWS Step Functions and DynamoDB. Emphasizes fast iteration without sacrificing trust via feature-flag rollouts, citation-required answers, abstention on low-confidence retrieval, regression query sets, and strong observability (request IDs, structured logs, latency/error monitoring).”

Jacqueline Zhang

Screened

Mid-level Machine Learning Engineer specializing in LLMs, fairness, and healthcare ML

Illinois, USA4y exp

“ML/NLP practitioner with a master’s thesis focused on domain-adaptive knowledge distillation for LLMs (LLaMA2/sheared LLaMA), showing improved perplexity and ROUGE-L on biomedical data. Also built real-world data linking and search systems: integrated ClinicalTrials.gov with FAERS using fuzzy matching + embeddings, and delivered an LLM-powered FAQ recommender at Hyperledger using sentence-transformers, FAISS, and fine-tuning to mitigate embedding drift.”

“ML/AI engineer with experience at Uber and Scale AI, focused on customer service automation across both classical NLP and generative AI systems. Has owned systems from experimentation through production on AWS, including LLM fine-tuning, RAG optimization, safety evaluation, and internal Python platform tooling that improved consistency and engineering velocity.”

Dheeraj Kumar

Screened

Intern Data Scientist specializing in marketing analytics and data engineering

Tucson, Arizona2y exp

“AI/LLM practitioner with internships at Dell Technologies and Roche who built and deployed a healthcare-focused "Doctor LLM" by fine-tuning Meta Llama 3.2 on healthcaremagic.json, emphasizing safety guardrails to prevent harmful medical advice. Experienced in productionizing AI workflows with monitoring, testing, and orchestration (Airflow, Kubernetes), and in delivering AI-agent-driven competitive landscape insights to non-technical business stakeholders.”

Asrith Velireddy

Screened

Mid-level AI/ML Engineer specializing in MLOps, LLMs, and scalable ML systems

Harrison, NJ4y exp

“ML/LLM engineer at Adobe who deployed a transformer-based personalization and campaign-targeting recommender system end-to-end, including PySpark/Airflow pipelines processing 12M+ events/day and containerized inference on AWS SageMaker (Docker/Kubernetes). Also has hands-on LLM workflow experience (RAG, semantic search, prompt optimization, hallucination mitigation) with a metrics-driven approach to reliability, drift monitoring, and reproducible retraining via MLflow.”

Jingyao Chen

Screened

Junior Backend/Platform Engineer specializing in AI microservices and cloud-native systems

Pittsburgh, PA2y exp

“Cofounder at MeowyAI who shipped a production multimodal (vision/voice/text) AI task manager using Gemini, tackling real-world issues like hallucinations, tool-calling safety, and RAG-based preference memory. Also built a production multi-agent RAG system orchestrated with LangGraph (and contributes to LangChain), with strong emphasis on latency optimization, observability (OpenTelemetry), and rigorous testing/evaluation including A/B tests and adversarial prompting.”

“Unity/C# gameplay engineer from Roku who led and shipped a cross-platform real-time multiplayer system spanning Meta Quest VR and iOS/Android, including AI/LLM-driven NPC behavior. Reported strong post-launch outcomes (+40% VR retention, +25% engagement) with stable networking (server-authoritative, delta compression/prediction) and robust debugging/observability via logging and replay tools.”

“Seed-stage startup engineer owning features end-to-end across full-stack development, DevOps, rollout, and post-launch maintenance. Built data ingestion and evaluation workflows for an LLM data-quality platform using Next.js, MongoDB, Postgres, and GCP Pub/Sub, with a strong focus on reliability, caching, and pragmatic performance improvements.”

“Built GenMedX, a multi-module clinical AI system for emergency department decision support spanning triage prediction, diagnosis, medication Q&A, and visit summarization. Stands out for combining medical LLM fine-tuning, RAG, and rigorous evaluation/monitoring to drive a major triage recall improvement from 38.5% to 76.6%, with a strong focus on safety, edge-case detection, and production reliability.”

“Technical lead who shipped a production GPT-4-powered customer support agent for Square, serving a large fintech customer base through a React chat interface with tool-using orchestration, guardrails, and live handoff paths. Brings strong real-world experience in agent reliability, evaluation, observability, and workflow orchestration using Temporal, Sidekiq, Pinecone, Datadog, and Snowflake.”

“Senior engineering executive and former VP of Architecture at Expedia who led a small, high-leverage architecture organization supporting an 8,000-person global engineering org. Brings a rare mix of executive people leadership and hands-on AI systems work, including OpenAI plugin integration, multi-agent booking architecture, and agentic fraud workflows that materially improved execution, automation, and customer-facing outcomes.”

“Product/UX designer with a CS/software engineering background at Microsoft (former intern, now full-time) who bridges design and implementation. Built Shiproom (a Twitch-like live-coding platform) end-to-end with a custom Atomic Design-based system, and has shipped impactful CRM improvements in Dynamics 365 for 60k+ support agents using TypeScript and C#. Also worked on a Microsoft Global Hackathon project integrating a Copilot-backed sign language translation model to reduce documentation friction for deaf support engineers.”

“Spatial computing software engineer focused on making Apple Vision Pro/visionOS accessible, including building VoiceOver and Live Captions features. Debugged a complex Live Captions issue involving dual audio inputs during FaceTime screen sharing by leveraging iOS implementation docs and creating concurrent audio sources; also has safety-critical testing experience from train control systems and is interested in pivoting into robotics.”

“AWS engineer who productionized an internal ML-driven data pipeline from a notebook prototype into a scalable, observable Python service (schema validation, deduplication, idempotency, safe retries, versioned transforms, CloudWatch alarms), reducing manual effort and improving data accuracy/trust. Experienced diagnosing workflow issues in real time (e.g., upstream schema changes) and partnering with account managers/support to unblock adoption of seller-facing Marketplace features by demonstrating reliability with concrete metrics.”

Sagnik Mazumder

Screened

Executive ML/AI Founder specializing in agentic analytics and data infrastructure

10y exp

“Founder of Photosphere Labs (agentic AI for ecommerce data synthesis/analysis) who worked directly with customers to scope, build, demo, and iterate LLM-based solutions, including an AI chat product for brand owners. Previously at Block, built and explained a nuanced causal inference/propensity model tied to Square POS integrations, translating model specs and outputs into business impact for varied client contexts.”

Anushka Bhagchandani

Screened

Intern Product & Software Engineer specializing in GenAI/LLM and e-commerce platforms

San Francisco, CA2y exp

“Software engineer (2+ years in India) and current GenAI intern who shipped LLM-powered review-writing enhancements at Myntra (Walmart-backed), using pilots and A/B tests to lift review quality by 5% in 30 days. Demonstrates strong LLM operations discipline (logging, dashboards, alerts, rollback) and fast incident response, plus experience delivering developer-focused workshops and public technical talks.”

Ranjani Salla

Screened

Mid-level AI/ML Engineer specializing in LLMs, FinTech, and Healthcare IT

USA5y exp

“Built production GenAI systems in both healthcare and financial services, including a Verily clinical platform and an Accenture financial Q&A product. Stands out for combining advanced RAG, fine-tuning, safety evaluation, and infrastructure engineering to deliver measurable gains in engagement, groundedness, hallucination reduction, and cost efficiency.”

Riya Devgan

Screened

Mid-level growth marketing and sales professional specializing in FinTech and D2C

New York, NY5y exp

“Outbound sales and partnerships candidate with experience at Indē Wild and HSBC, combining data-led prospecting with highly personalized messaging. They’ve converted senior decision-makers by using transaction and audience insights, and their creator-partnership outreach helped drive 50M+ impressions and support Indē Wild’s launch in Sephora US.”