Vetted Matplotlib Professionals

Tharun Chowdary Malepati

Screened

Mid-level AI/ML Engineer specializing in GenAI, NLP, and production MLOps

5y exp

“AI/LLM engineer who built and deployed a production healthcare RAG chatbot ("DoctorBot") with strict medical safety guardrails, an 85% confidence-gated verification layer, and latency optimizations that cut responses from ~8s to ~2–3s. Also worked on finflow.ai to generate finance/banking test cases from BRDs, collaborating closely with non-technical domain stakeholders, and has hands-on orchestration experience with LangChain/LangGraph and agentic evaluation/monitoring practices.”

“Analytics professional focused on procurement, supplier, and contract spend analytics, with hands-on experience using Snowflake SQL, Python, and Power BI to turn messy financial and vendor data into decision-ready reporting. They appear strongest in building reusable data workflows, defining business KPIs with finance/procurement partners, and validating results through reconciliation and stakeholder review.”

“Analytics-focused candidate from SWAP PM with hands-on experience turning messy onboarding and user behavior data into reliable funnel and retention reporting using SQL and Python. They owned an end-to-end onboarding improvement project, aligned stakeholders on metric definitions, and helped drive changes that reduced onboarding time by about 45%.”

“Full-stack engineer who has owned both institutional and personal products end-to-end, including Rutgers' myCommunity platform used by 70,000+ students. Particularly strong in production systems, data synchronization, authentication, and third-party API integrations, with a pragmatic approach to shipping, observability, and UI modernization.”

“Built and deployed a Unity-based, NSF-funded medical interaction system for the University of Houston MRI Lab, combining speech recognition, LLaMA-based function calling, and real-time simulation controls. Particularly strong in taking experimental AI systems from discovery through stabilization, with measurable impact including roughly 50% faster task completion than traditional point-and-click workflows.”

“AI/ML engineer with 9+ years of experience building production recommendation and LLM systems end-to-end, from experimentation through deployment, monitoring, and retraining. Stands out for combining strong MLOps discipline with practical GenAI/RAG implementation, including measurable impact such as ~25% higher engagement on an e-commerce recommender and nearly 30% faster knowledge retrieval from internal documents.”

“Early-career candidate with academic data science and machine learning project experience, including a YouTube comment sentiment analysis project comparing LSTM and GRU models. Demonstrates a collaborative working style, structured task planning, and careful review of final deliverables in team-based project settings.”

“ML/AI engineer with hands-on experience building healthcare and fraud-detection systems from experimentation through deployment, monitoring, and retraining. Stands out for combining real-time IoT pipelines, cloud-native MLOps, and GenAI/RAG in regulated healthcare settings, with reported impact including reduced emergency response times and a 25% reduction in manual diagnosis time.”

Tony Monckton

Screened

Senior Unity VR/AR Programmer specializing in Meta Quest and real-time 3D graphics

London, UK12y exp

“Unity/VR developer who shipped a Meta Quest 2 immersive 360 training experience for Staffordshire Police as a solo programmer, including biometric gaze/reaction tracking and real-time data capture to an HTTP endpoint. Also building a Tomb Raider-like sci-fi adventure demo (Nexus 7) featuring FSM-driven character logic, motion-capture animation, custom controller optimization, and spline-following AI movement.”

Kathan Patel

Screened

Mid-level Generative AI Developer specializing in Python and LLM applications

5y exp

“Currently working on Kavia AI, an end-to-end AI coding platform that lets users generate enterprise applications from prompts and existing codebases via SCM integrations. The candidate has hands-on experience across the GenAI stack—prompt engineering, LangGraph-based multi-agent orchestration, RAG, knowledge graphs, FastAPI, and AWS monitoring—with a focus on making software creation accessible to non-technical users.”