Vetted A/B Testing Professionals

“Worked on taking an LLM-based system at Soundmakr from prototype to production by adding prompt constraints, validation/guardrails, deterministic ranking, and robust logging/monitoring with feedback loops. Also partnered with product/marketing during an internship on Thea: Study Smart to analyze onboarding drop-offs and run A/B tests on AI-driven flows, translating results into actions that improved retention and conversion.”

“Performance marketing specialist with hands-on ownership of $50K+/month spend on the AdOn Network at RhythmOne, focused on driving new-user growth and on-site engagement. Known for rigorous, variable-isolated testing across keywords, placements, and ad copy, plus clear client reporting tied to engagement and efficiency metrics.”

“Performance marketer managing high-spend, multi-platform paid media for major brands (e.g., Navistar, Buick), with end-to-end ownership from strategy to reporting. Uses multivariate testing and trend-based budget reallocations to drive measurable lifts (27–60% KPI improvements) and significant outperformance (2.8x vs forecast), and has experience removing conversion friction by replacing lead forms with landing page + chat-based flows.”

“Built and productionized an LLM-powered financial intelligence and forecasting platform at Northern Trust using a RAG architecture (LangChain + Hugging Face + FAISS) with end-to-end MLOps (Docker/Kubernetes, Airflow, MLflow). Emphasized regulatory-grade explainability (SHAP/Power BI) and hallucination control (retrieval-only grounding), achieving ~30% forecasting accuracy improvement and ~65% reduction in analyst research time, with sub-second inference and 95% uptime on EKS/AKS.”

“Strategic sales and partnerships professional (Adaptavist/Atlassian partner ecosystem) who closed and expanded an enterprise integration partnership with NASDAQ around a custom monday.com integration. Strong in partner-led GTM and activation loops, leveraging warm networks to accelerate sales cycles and using experimentation to improve demo attendance, qualification, and forecast accuracy (including $110K USD closed-won from pipeline).”

“Built and deployed a GPT-4 + Pinecone RAG system that lets users query large internal document collections with grounded, cited answers. Demonstrates strong applied LLM engineering (chunking experiments, hallucination controls, metadata recency boosting) plus production-minded evaluation/monitoring and performance tuning (rate-limit mitigation via pooling/batching). Also effective at translating complex AI concepts to non-technical stakeholders through prototypes and live demos, helping secure client sponsorship.”

“Built a production AI fraud/risk scoring platform at BlueArc that ingests web business/product/site data, generates text+image embeddings, and connects entities in a graph to detect reuse patterns and links to known bad actors. Optimized for scale with incremental graph re-scoring and delivered investigator-friendly explainability by surfacing the exact signals/relationships behind each score; orchestrated workflows with Airflow and GCP event-driven components (Pub/Sub, Dataflow, Cloud Run) and has recent LLM workflow orchestration experience (retrieval, prompting, scoring).”

“Frontend/product engineer who has led end-to-end builds across automotive and healthcare: created a multi-tenant, high-performance Next.js luxury inventory platform and a secure, Stripe-powered sick-note workflow integrated with an EMR. Known for data-driven UX decisions (A/B testing) and pragmatic modernization of critical systems (3DS2 upgrade) with measurable conversion and risk improvements.”

“Deployed a real-time LLM-driven call center summarization and agent-assist platform at Fifth Third Bank, combining transformer models (BERT/GPT) with FastAPI inference on AKS and vector storage (ChromaDB/PostgreSQL). Emphasizes production-grade reliability (autoscaling, CI/CD, monitoring) and measurable evaluation (A/B testing), and translates model outputs into business-facing Power BI insights for call center leadership.”

“LLM/RAG practitioner building clinician-facing AI search and Q&A inside EHR workflows, focused on trust, latency, and safety (grounded answers with citations, PHI controls, encryption/audit logs). Demonstrated real-time incident response for production LLM systems (e.g., fixing a metadata-filter deployment regression to prevent irrelevant results/cross-patient leakage) and strong demo/enablement skills for mixed technical and clinical stakeholders; also shipped a multi-model RAG tool at OrbeX Labs with upload/search/audit features for day-to-day adoption.”

“ML/AI engineer who built and productionized an NLP system at PurevisitX, orchestrating end-to-end ML workflows with Airflow (S3 ingestion through auto-retraining) and optimizing for drift and low-latency inference. Also partnered with Citibank risk teams on a fraud detection model, translating results via dashboards and iterating thresholds based on stakeholder feedback.”

“Built a production LLM-RAG system at McKesson to let internal healthcare operations teams query large volumes of unstructured operational documents via natural language with source-backed answers, designed with HIPAA/FHIR compliance in mind. Demonstrated strong production engineering across hallucination mitigation, retrieval quality tuning, and latency/scalability optimization, using LangChain/LangGraph and Airflow plus rigorous evaluation/monitoring practices.”

“Lifecycle/CRM marketer with hands-on Braze automation experience, running cross-channel (email + push) onboarding and milestone campaigns for an app-based content product. Demonstrated strong activation metrics on Day 0 and drove a 10% week-over-week churn reduction by partnering with Customer Service on winback save-rate and scripting tests.”

“UX designer (3 years) with a UI engineering background who has built an end-to-end accessible STEM learning experience for blind/visually impaired students, including a MathML-to-MathSpeak parsing solution and multimodal feedback (screen reader, braille keyboard, haptics). Also simplified an AI-driven scoring/onboarding workflow at Founderway.ai using progressive disclosure and iterative usability testing tied to measurable improvements.”

“ML/MLOps practitioner from Discover Financial who built and deployed a real-time AI fraud detection platform (LSTM + VAE) on AWS SageMaker with Docker/FastAPI and Jenkins-driven CI/CD. Demonstrated measurable impact (30% accuracy lift, 25% fewer false alerts) and deep expertise in class-imbalance mitigation, drift monitoring, and orchestration (Airflow/Kubeflow), plus strong stakeholder adoption via Power BI dashboards for fraud/compliance teams.”

“Software/ML engineer who built a production automated job-finding and cold-email personalization system for Fortune 500 outreach, using JobSpy for dynamic scraping, LangChain orchestration, and LLM+vector DB semantic search with grounding/relevance metrics and guardrails. Also delivered a predictive investment analytics platform for financial advisors, communicating results via Tableau dashboards and portfolio KPIs like Sharpe ratio and drawdowns.”

“ML/AI engineer (TCS) who built and productionized a customer segmentation and personalized-offer recommendation pipeline end-to-end (data cleaning/feature engineering/clustering through Flask API deployment in Docker with monitoring). Emphasizes reliability and operational rigor via validation checks, periodic retraining, model/API versioning, and latency optimization, and has experience translating marketing KPIs into usable dashboards for non-technical teams.”

“Console game certification-focused QA tester with strong PlayStation (PS4/PS5) TRC experience and solid Nintendo LOT check exposure, including NDI and Nintendo Developer Center submission tracking. Works deadline-driven submissions using prioritized templates/checklists and leverages internal AI tools for reporting, documentation lookup, and certification risk/go-no-go recommendations.”

“Built and productionized an LLM/RAG question-answering service over technical documentation, focusing on retrieval quality (reranking + IR metrics), latency, and scaling. Experienced orchestrating end-to-end ETL/ML workflows with Airflow/Prefect/AWS Step Functions and improving reliability via parallelism, retries, and shadow testing. Also delivered an explainable healthcare risk-flagging classifier with a stakeholder-friendly dashboard for a non-technical program manager.”

“ML/AI engineer who deployed a real-time, edge-based computer-vision pipeline for produce recognition in retail self-checkout to reduce shrink. Demonstrates strong end-to-end production chops: multi-camera data calibration/sync, ranking-based modeling for fine-grained classes, latency-focused optimization, and continuous A/B testing/monitoring with guardrails. Experienced with ML orchestration (Kubeflow Pipelines, Airflow) and CI/CD via GitHub Actions, and collaborates closely with store operations to make interventions usable in the checkout flow.”

“Machine learning/NLP engineer with deep Azure stack experience (Data Factory, Databricks/Spark, Delta Lake, Azure OpenAI, Azure AI Search) who built end-to-end production systems for semantic clustering, entity resolution, and hybrid search. Demonstrated measurable gains from embedding fine-tuning (~15% retrieval precision, ~10–12% nDCG@10) and designed scalable, quality-checked pipelines with MLOps best practices.”

“Contract/freelance paid media specialist who personally managed a high-spend ($50K–$80K/month) ecommerce cycling brand across Meta and Google. Drove measurable gains including ROAS improvement (~3.2 to ~5.2), ~$330K+ tracked revenue on an ~$80K peak-month spend, and ~20% CPA reduction through structured creative/audience testing, feed optimization, and profitability-focused campaign management.”

“Enterprise customer success / partner lead in performance marketing managing multi-million-dollar spend, focused on ROAS/CPA optimization and scaling adoption. Has led cross-functional Product/Engineering efforts (pixel event tracking + custom model) to improve campaign performance and influenced reporting roadmap via structured partner feedback (QBRs/check-ins). Experienced in land-and-expand motions, partnering with Sales to grow accounts by tying expansion directly to measurable value.”

“Game economy/product designer with hands-on experience tuning F2P word/puzzle games (Crossword Jam, Word Trip). Introduced internal currencies and wallet-based reward personalization to control coin inflation and protect IAP/rewarded ads performance, backed by Google Sheets modeling, cohort analysis, and competitor benchmarking (Royal Match, Wordscapes). Based in Santa Clara, CA and prefers remote work with occasional travel.”