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Vetted Tableau Professionals
Pre-screened and vetted.
Mid-level Data Scientist / GenAI & ML Engineer specializing in LLM apps and MLOps
Senior Data Engineer specializing in cloud data platforms and real-time streaming
Mid-level AI/ML Engineer specializing in LLM infrastructure and FinTech ML platforms
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level AI/ML Engineer specializing in LLMs, RAG, and scalable MLOps
Senior Software Engineer specializing in cloud architecture and machine learning
Mid-level AI/ML Engineer specializing in generative AI, LLMs, and MLOps
Mid-level Software Engineer specializing in backend APIs, data pipelines, and cloud microservices
Senior Data Engineer specializing in cloud-native data platforms and streaming pipelines
Mid-level Applied AI Engineer specializing in LLMs, MLOps, and real-time AI systems
Mid-level AI/ML Engineer specializing in LLMs, multilingual NLP, and low-latency MLOps
Senior AI/ML & Data Scientist specializing in NLP, knowledge graphs, and semantic search
Senior AI/ML Engineer specializing in LLM agents, RAG, and production ML systems
Mid-level Machine Learning Engineer specializing in Generative AI and LLM applications
Director-level Strategy Consulting Manager specializing in growth strategy and M&A
Thazim Banu Shaffee
Engineering Manager specializing in payments, risk, and high-scale distributed systems
“Engineering leader/player-coach on a risk core transaction platform (payments/branded checkout) who led major migrations from a monolithic stack to microservices, including API contract redesign and performance improvements (reported ~500ms latency reduction). Experienced running high-stakes production incidents (upgrade-related outage/degradation) end-to-end with RCA and rollout-process changes, and has accelerated delivery via documentation/tooling (audit sign-off cycle reduced from ~3 sprints to ~1).”
Abhijay Sai Paladugu
Junior Data Scientist specializing in LLM agents, RAG, and reinforcement learning
“McKinsey practitioner who built and deployed production LLM systems for consultants/clients, including a Power BI-integrated multi-agent chatbot (RAG + text-to-SQL + formatting) with custom Python orchestration, verification loops, and a 100+ case eval set achieving ~95% consistency. Also delivered a taxonomy-mapper agent that standardized inconsistent labeling for C-suite stakeholders, cutting a process from >2 weeks to <30 minutes through demos and business-focused communication.”
Sai Chandra Bandi
Mid-level AI/ML Engineer specializing in Generative AI, LLM alignment, and RAG
“Built and productionized a real-time enterprise RAG pipeline to improve factual accuracy and reduce LLM hallucinations by grounding responses in constantly changing internal knowledge bases (policies, manuals, FAQs). Experienced in orchestrating end-to-end ML workflows (Airflow/Kubernetes), handling messy multi-format data with schema enforcement (Pydantic/Hydra), and maintaining freshness via streaming incremental embeddings plus batch refresh. Also delivers applied ML solutions with non-technical teams (marketing/CRM) for segmentation and personalized engagement.”
Prasanth Peddireddy
Entry-level Supply Chain & Test Engineer specializing in warehouse automation and robotics
“P&G operator who is also building and selling an AI receptionist (voice agent) SaaS for healthcare/service clinics, using EHR + calendar API compatibility to target accounts and letting the Voice AI run parts of the demo to prove value. Has already closed and deployed to two clients in the last two months, with production impact via reduced front-desk overhead and automated scheduling/FAQs, and brings a structured, scalable deployment/process mindset from global WMS rollouts.”