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Vetted A/B Testing Professionals
Pre-screened and vetted.
SASIREKHA GULIPALLI
Mid-level Data Analyst specializing in procurement, supply chain analytics, and applied machine learning
“Strategic sourcing professional specializing in seasonal apparel supply chains, combining Coupa/JD Edwards analytics with Excel/Python modeling and Power BI dashboards to drive cost reduction and OTIF gains. Notable for rapid mitigation of a 10-day factory delay affecting 12 holiday SKUs (preserved 95% of revenue) and for automating PO workflows to cut cycle time by 4.2 days and improve OTIF by 15%.”
Rushir Bhavsar
Intern AI/ML Engineer specializing in LLMs, MLOps, and distributed training
“Founding AI engineer (June 2024) at Talon Labs who built and productionized an LLM-powered chatbot for interacting with proprietary supply-chain documents, deployed at large scale (25–100,000 users). Experienced with RAG/LLM orchestration (LangChain, LlamaIndex, Groq AI) and production ops tooling (Kubernetes, Docker, Kubeflow, Airflow), with a metrics-driven approach to evaluation, observability, and stakeholder alignment.”
Jax Diagana
Senior AI Engineer specializing in forward-deployed voice agents and incident-response automation
“FDE at Bland.ai and founder of Fi (incident-response agent) who routinely takes LLM/agentic concepts from prototype to production. Has hands-on experience reverse-engineering undocumented systems to deliver integrations, building LLM testbeds for voice-agent reliability, and rapidly shipping RAG/semantic search solutions (e.g., Confluence runbooks) after deep customer discovery with DevOps/SRE teams.”
Sana Khan
Mid-level AI/ML Engineer specializing in MLOps, LLMs, and real-time inference in FinTech
“ML/LLM engineer who has deployed a production LLM-powered assistant for intent classification and query routing (order recommendation/support deflection), combining BERT fine-tuning with an embedding-based retrieval layer and optimizing for low-latency inference. Experienced with end-to-end reliability practices—Airflow-orchestrated ETL, data validation/alerting, MLflow experiment tracking, and iterative improvements driven by user feedback and monitoring.”
Chandra Shekar Akkandra
Mid-level AI/ML Engineer specializing in fraud detection and risk analytics in Financial Services
“Finance-domain ML/LLM engineer who has shipped production systems including a RAG-based financial insights assistant with a custom post-generation validation layer that verifies atomic claims against retrieved source text to prevent hallucinations in compliance-critical workflows. Also built large-scale MLOps automation on AWS using Kubeflow + MLflow + CI/CD for fraud detection and credit risk models processing 500M+ transactions/day with a 99.99% uptime goal, and partnered closely with JP Morgan risk/compliance stakeholders on NLP-driven compliance monitoring.”
Narendra R
Senior Full-Stack Java Developer specializing in microservices and cloud platforms
“Backend engineer focused on scalable Python/Flask services and high-performance PostgreSQL/SQLAlchemy systems, with demonstrated wins like reducing N+1-driven response times to under 200ms and cutting P95 latency below 1s via background queues and caching. Has production experience operationalizing ML models as Dockerized APIs on AWS (S3/Lambda) with monitoring (CloudWatch/ELK), plus robust multi-tenant isolation using JWT-driven tenant context and row-level security.”
Abdul Mohammed
Mid-level Data Analyst specializing in healthcare and financial analytics
“Built and productionized an LLM-powered clinical documentation and insights pipeline at Cardinal Health using LangChain + GPT-4 with RAG to summarize long clinical notes, extract medication/dosage entities, and generate structured SQL-ready outputs for downstream analytics. Emphasizes clinical reliability via labeled benchmarking (precision/recall/F1), shadow deployments, clinician human-in-the-loop review, and ongoing monitoring/orchestration with Airflow, Lambda, S3, Postgres, and Power BI.”
Meghanath kethireddy
Mid-level Full-Stack/Backend Engineer specializing in Java microservices and cloud platforms
“PayPal ML/AI practitioner who built and productionized a hybrid recommendation engine (BERT/LLM embeddings + collaborative filtering + XGBoost ranking) on AWS with end-to-end MLOps and orchestration. Addressed real-world issues like cold start and embedding latency (ONNX, clustering, caching, PySpark/Delta Lake) and drove a 27% lift in upsell conversion via A/B testing and stakeholder collaboration with marketing.”
Chakravarthy V P
Executive AI Consultant/CTO specializing in Agentic AI, GenAI, and cloud-native data platforms
“Bootstrapped founder and CTO of C4Scale, a 2.5-year-old services-led company delivering MVP-to-scale product/platform builds for high-value clients across 5+ countries (10+ projects). Strong fit for roles blending scalable SaaS platform engineering, technical org leadership, and practical AI adoption, with clear awareness of the operational and GTM challenges of scaling into enterprise.”
Annie Suzan
Mid Software Engineer specializing in machine learning and real-time data systems
“Hands-on implementation-focused candidate with experience owning cloud deployments and putting LLM/RAG workflows into production. They stand out for combining customer-facing deployment ownership with practical AI systems work, including retrieval tuning, hallucination mitigation, production incident response, and document-processing pipelines for messy real-world inputs.”
Ram Jayesh Parekh
Junior Data Analyst specializing in ML, NLP, and cloud data pipelines
“Built and deployed a GenAI-powered PhD career intelligence platform at NYU that maps academic backgrounds to career paths and converts long academic CVs into job-ready resumes. Stands out for treating LLM systems as structured production pipelines—combining NLP extraction, embeddings, orchestration, and AWS deployment—to improve recommendation quality and cut resume preparation time by 70%.”
Dhriti Kanchan
Mid-level Data Analyst specializing in healthcare and financial analytics
“Analytics-focused candidate with hands-on experience turning messy CRM, e-commerce, payments, and support data into trusted reporting datasets using SQL and Python. They have owned end-to-end churn and retention analytics work, including RFM-based segmentation, dashboard delivery, and metric standardization across sales, marketing, and finance.”
“Built and deployed a production RAG-based internal knowledge assistant that let analysts query company documents in natural language, using LangChain/LangGraph with Pinecone and a FastAPI service for integration. Emphasizes reliability in production through hallucination mitigation (retrieval tuning + prompt guardrails) and measurable evaluation/monitoring (accuracy, latency, task completion, hallucination rate), iterating based on user feedback.”
Diwita Banerjee
Mid-level AI/ML Engineer specializing in LLMs, RAG, and enterprise AI
“Built an enterprise RAG-based document intelligence system at Freddie Mac for regulatory and financial documents, helping analysts cut search time from hours to minutes while improving retrieval accuracy by ~30%. Stands out for combining LLM product delivery with compliance-grade auditability, production monitoring, and scalable Python/FastAPI service design.”
Carey Fox
Director-level CRM and lifecycle marketing leader specializing in multi-channel strategy
“CRM/lifecycle marketing strategist with hands-on ownership of campaign strategy, audience definition, QA oversight, and performance analysis across onboarding, re-engagement, nurture, retargeting, and winback programs. Particularly strong in experimentation design, offer testing, and using behavioral/purchase data to personalize messaging and improve sales outcomes, though not a direct Braze builder.”
Eugene Nelepko
Executive growth leader specializing in AI-powered SaaS, marketplaces, and e-commerce
“Growth leader with strong zero-to-one and systems-building experience across e-commerce and retail media. Most notably, they proposed and launched a new retail media division from scratch, presold demand before product build, and scaled it to $1.5M ARR with 85% margin, while also building data-driven lifecycle and acquisition systems that materially improved activation and CAC efficiency.”
Nikitha Ramesh
Junior Product Manager and AI/ML engineer specializing in enterprise SaaS and cloud AI
“Growth-focused B2B SaaS operator with hands-on experience improving enterprise adoption for a cloud governance and FinOps platform. They combine customer discovery, ROI-driven messaging, automation, and funnel instrumentation to improve conversion and handoffs, citing an 18% lift in enterprise adoption and roughly $200K-$3M in influenced pipeline.”
Pranav Iyer
Mid-level UX Engineer specializing in B2B SaaS, FinTech, and healthcare products
“Product/UX designer with hands-on front-end implementation experience who has worked across both consumer and enterprise contexts, including a veterinary hospital funnel redesign and an AML fraud detection system. Stands out for tying UX decisions to measurable business outcomes, including a 17% reduction in dropoff after redesigning package selection and validating changes through usability testing.”
“AI/full-stack engineer in gaming analytics who joined Omnic.ai at a 2-person stage, helped grow with the company, and built both backend and frontend for real-time gameplay analysis products. He combines computer vision production experience with LLM/RAG systems work, and has already led 4 employees while shipping 12 models in a fast-moving startup environment.”
Brent Cook
Director-level product leader specializing in AI-powered search and discovery
“Former high school teacher turned product leader with deep experience in EdTech, scholarly search/discovery, and mobile content platforms. They’ve led complex end-to-end launches, including a direct-to-consumer app storefront delivered on a 7-month timeline and AI-powered research discovery features for a 5-billion-record search platform, while bringing a strong human-centered, accessibility-first perspective to AI products.”
Jasmine Peel
Senior CRM and eCommerce marketing professional specializing in retention and lifecycle strategy
“CRM and lifecycle marketer with strong DTC/eCommerce experience at Fenty Beauty, spanning strategy through hands-on execution across email, SMS, and push. Stands out for combining platform expertise in Klaviyo/Attentive with data-driven segmentation, retention strategy, and team leadership—highlighted by a VIP re-engagement campaign that converted about 30% of a targeted at-risk audience and lifted AOV.”
Abhishek Pravin Mane
Mid-Level Full-Stack Software Engineer specializing in FinTech and Healthcare SaaS
“Customer-facing technical professional with experience supporting LLM/agentic-style workflows and complex integrated systems (APIs, backend logic, databases). Partnered with sales/customer teams at Radix Health to onboard new clients in phased prototypes, translating non-technical requirements into technical scope and implementing core product changes to tailor the appointment-booking solution for providers.”
Sharath Bandi
Mid-level Generative AI Engineer specializing in LLMs, RAG, and multimodal generation
“Open-source JavaScript contributor focused on performance and maintainability in data visualization libraries—refactored legacy ES5 into modular ES6, added tests/docs, and delivered ~30% faster load times with positive community adoption. Also optimized a React dashboard (~40% load-time reduction) and took ownership in an ambiguous AI product initiative by setting milestones, standing up an initial ML pipeline, and shipping a prototype in ~6 weeks that became the basis for production.”