Hire the Best Supervised Learning Specialists

𝐏𝐲𝐭𝐡𝐨𝐧 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 𝐚𝐧𝐝 𝐓𝐮𝐭𝐨𝐫 | 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 | 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐒𝐩𝐞𝐜𝐢𝐚𝐥𝐢𝐬𝐭 | 𝐋𝐚𝐫𝐠𝐞 𝐥𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐌𝐨𝐝𝐞𝐥𝐬 (𝐋𝐋𝐌𝐬) 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭 | 𝐑𝐚𝐠 𝐚𝐧𝐝 𝐅𝐢𝐧𝐞-𝐭𝐮𝐧𝐢𝐧𝐠 | 𝐀𝐈 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 | 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬 𝐆𝐫𝐞𝐞𝐭𝐢𝐧𝐠 , 𝐈’𝐦 𝐕𝐢𝐠𝐧𝐞𝐬𝐡𝐰𝐚𝐫𝐚𝐧 𝐚𝐧 𝐀𝐈 𝐢𝐧𝐧𝐨𝐯𝐚𝐭𝐨𝐫 𝐝𝐫𝐢𝐯𝐢𝐧𝐠 𝐫𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐢𝐦𝐩𝐚𝐜𝐭 𝐭𝐡𝐫𝐨𝐮𝐠𝐡 𝐝𝐞𝐞𝐩 𝐞𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞 𝐢𝐧 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠, 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠, 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧, 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈, 𝐏𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬, 𝐚𝐧𝐝 𝐋𝐋𝐌𝐬. 𝐈’𝐯𝐞 𝐛𝐮𝐢𝐥𝐭 𝐜𝐮𝐭𝐭𝐢𝐧𝐠-𝐞𝐝𝐠𝐞 𝐀𝐈 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 𝐟𝐨𝐫 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞𝐬, 𝐬𝐭𝐚𝐫𝐭𝐮𝐩𝐬, 𝐚𝐧𝐝 𝐡𝐢𝐠𝐡-𝐟𝐫𝐞𝐪𝐮𝐞𝐧𝐜𝐲 𝐭𝐫𝐚𝐝𝐢𝐧𝐠, 𝐜𝐨𝐧𝐬𝐢𝐬𝐭𝐞𝐧𝐭𝐥𝐲 𝐡𝐞𝐥𝐩𝐢𝐧𝐠 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬𝐞𝐬 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞, 𝐨𝐩𝐭𝐢𝐦𝐢𝐳𝐞, 𝐚𝐧𝐝 𝐬𝐜𝐚𝐥𝐞 𝐭𝐡𝐞𝐢𝐫 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬 𝐚𝐧𝐝 𝐑&𝐃 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡 🚨 𝐖𝐡𝐲 𝐂𝐥𝐢𝐞𝐧𝐭𝐬 𝐇𝐢𝐫𝐞 𝐌𝐞 ✅ 𝐅𝐮𝐥𝐥-𝐭𝐢𝐦𝐞 𝐅𝐫𝐞𝐞𝐥𝐚𝐧𝐜𝐞𝐫 — 𝟓𝟎+ 𝐡𝐫𝐬/𝐰𝐞𝐞𝐤 | 𝐅𝐥𝐞𝐱𝐢𝐛𝐥𝐞 𝐚𝐜𝐫𝐨𝐬𝐬 𝐚𝐥𝐥 𝐭𝐢𝐦𝐞 𝐳𝐨𝐧𝐞𝐬. ✅ 𝐄𝐧𝐝-𝐭𝐨-𝐄𝐧𝐝 𝐎𝐰𝐧𝐞𝐫𝐬𝐡𝐢𝐩 — 𝐟𝐫𝐨𝐦 𝐛𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐫𝐨𝐛𝐮𝐬𝐭 𝐝𝐚𝐭𝐚 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 𝐭𝐨 𝐝𝐞𝐩𝐥𝐨𝐲𝐢𝐧𝐠 𝐬𝐜𝐚𝐥𝐚𝐛𝐥𝐞 𝐌𝐋 𝐦𝐨𝐝𝐞𝐥𝐬 𝐨𝐧 𝐭𝐡𝐞 𝐜𝐥𝐨𝐮𝐝. ✅ 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐑𝐞𝐚𝐝𝐲 𝐑𝐞𝐬𝐮𝐥𝐭𝐬 — 𝐧𝐨 𝐦𝐨𝐫𝐞 “𝐰𝐨𝐫𝐤𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐥𝐚𝐛, 𝐟𝐚𝐢𝐥𝐬 𝐢𝐧 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧.” 𝐌𝐲 𝐀𝐈 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 𝐦𝐚𝐢𝐧𝐭𝐚𝐢𝐧 𝟗𝟗.𝟗% 𝐮𝐩𝐭𝐢𝐦𝐞 𝐚𝐧𝐝 𝐝𝐞𝐥𝐢𝐯𝐞𝐫 𝐦𝐞𝐚𝐬𝐮𝐫𝐚𝐛𝐥𝐞 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐢𝐦𝐩𝐚𝐜𝐭. 𝐝𝐨𝐧’𝐭 𝐣𝐮𝐬𝐭 𝐝𝐞𝐥𝐢𝐯𝐞𝐫 𝐦𝐨𝐝𝐞𝐥𝐬 — 𝐈 𝐝𝐞𝐥𝐢𝐯𝐞𝐫 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐭𝐡𝐚𝐭 𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞 𝐬𝐞𝐚𝐦𝐥𝐞𝐬𝐬𝐥𝐲 𝐰𝐢𝐭𝐡 𝐲𝐨𝐮𝐫 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬, 𝐞𝐧𝐬𝐮𝐫𝐢𝐧𝐠 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞, 𝐫𝐞𝐥𝐢𝐚𝐛𝐢𝐥𝐢𝐭𝐲, 𝐚𝐧𝐝 𝐥𝐨𝐧𝐠-𝐭𝐞𝐫𝐦 𝐬𝐜𝐚𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲. 𝐒𝐩𝐞𝐜𝐢𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 & 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧 𝐢𝐧 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲 ✅ 𝐀𝐈 & 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐄𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞 — 𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐭 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐮𝐬𝐢𝐧𝐠 𝐏𝐲𝐭𝐡𝐨𝐧, 𝐓𝐞𝐧𝐬𝐨𝐫𝐅𝐥𝐨𝐰, 𝐏𝐲𝐓𝐨𝐫𝐜𝐡, 𝐚𝐧𝐝 𝐬𝐜𝐚𝐥𝐚𝐛𝐥𝐞 𝐌𝐋 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞𝐬 𝐭𝐚𝐢𝐥𝐨𝐫𝐞𝐝 𝐟𝐨𝐫 𝐫𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐧𝐞𝐞𝐝𝐬. ✅ 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 & 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 — 𝐃𝐞𝐬𝐢𝐠𝐧𝐢𝐧𝐠 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞𝐝 𝐝𝐚𝐭𝐚 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬, 𝐟𝐞𝐚𝐭𝐮𝐫𝐞 𝐬𝐭𝐨𝐫𝐞𝐬, 𝐚𝐧𝐝 𝐄𝐓𝐋 𝐩𝐫𝐨𝐜𝐞𝐬𝐬𝐞𝐬 𝐟𝐨𝐫 𝐡𝐢𝐠𝐡-𝐯𝐨𝐥𝐮𝐦𝐞, 𝐫𝐞𝐚𝐥-𝐭𝐢𝐦𝐞 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬. ✅ 𝐂𝐥𝐨𝐮𝐝 & 𝐌𝐋𝐎𝐩𝐬 — 𝐃𝐞𝐩𝐥𝐨𝐲𝐢𝐧𝐠 𝐞𝐧𝐝-𝐭𝐨-𝐞𝐧𝐝 𝐌𝐋 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 𝐨𝐧 𝐀𝐖𝐒 | 𝐆𝐂𝐏 | 𝐀𝐳𝐮𝐫𝐞, 𝐥𝐞𝐯𝐞𝐫𝐚𝐠𝐢𝐧𝐠 𝐃𝐨𝐜𝐤𝐞𝐫, 𝐅𝐚𝐬𝐭𝐀𝐏𝐈, 𝐚𝐧𝐝 𝐂𝐈/𝐂𝐃 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 𝐟𝐨𝐫 𝐬𝐞𝐚𝐦𝐥𝐞𝐬𝐬 𝐬𝐜𝐚𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲. ✅ 𝐀𝐈 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧 — 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐧𝐠 𝐋𝐋𝐌𝐬, 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈, 𝐍𝐋𝐏, 𝐚𝐧𝐝 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧 𝐭𝐨 𝐩𝐮𝐬𝐡 𝐭𝐫𝐚𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐢𝐧𝐭𝐨 𝐭𝐡𝐞 𝐧𝐞𝐱𝐭 𝐞𝐫𝐚 𝐨𝐟 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞. ✅ 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐨𝐮𝐬 𝐈𝐦𝐩𝐫𝐨𝐯𝐞𝐦𝐞𝐧𝐭 — 𝐄𝐱𝐩𝐞𝐫𝐢𝐦𝐞𝐧𝐭𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐜𝐮𝐭𝐭𝐢𝐧𝐠-𝐞𝐝𝐠𝐞 𝐫𝐞𝐬𝐞𝐚𝐫𝐜𝐡, 𝐨𝐩𝐭𝐢𝐦𝐢𝐳𝐢𝐧𝐠 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞, 𝐚𝐧𝐝 𝐞𝐧𝐬𝐮𝐫𝐢𝐧𝐠 𝐞𝐯𝐞𝐫𝐲 𝐦𝐨𝐝𝐞𝐥 𝐞𝐯𝐨𝐥𝐯𝐞𝐬 𝐰𝐢𝐭𝐡 𝐧𝐞𝐰 𝐝𝐚𝐭𝐚 𝐚𝐧𝐝 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲 𝐭𝐫𝐞𝐧𝐝𝐬. 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 ✅𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐌𝐋 & 𝐀𝐈 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 — 𝐃𝐞𝐬𝐢𝐠𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐝𝐞𝐩𝐥𝐨𝐲𝐢𝐧𝐠 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐦𝐨𝐝𝐞𝐥𝐬, 𝐫𝐞𝐜𝐨𝐦𝐦𝐞𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐬𝐲𝐬𝐭𝐞𝐦𝐬, 𝐚𝐧𝐝 𝐜𝐥𝐚𝐬𝐬𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧/𝐫𝐞𝐠𝐫𝐞𝐬𝐬𝐢𝐨𝐧 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 𝐮𝐬𝐢𝐧𝐠 𝐏𝐲𝐭𝐡𝐨𝐧, 𝐓𝐞𝐧𝐬𝐨𝐫𝐅𝐥𝐨𝐰, 𝐏𝐲𝐓𝐨𝐫𝐜𝐡, 𝐚𝐧𝐝 𝐒𝐜𝐢𝐤𝐢𝐭-𝐥𝐞𝐚𝐫𝐧. ✅ 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 & 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 — 𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞𝐝 𝐄𝐓𝐋 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬, 𝐟𝐞𝐚𝐭𝐮𝐫𝐞 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬, 𝐚𝐧𝐝 𝐝𝐚𝐭𝐚 𝐩𝐫𝐞𝐩𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠 𝐟𝐨𝐫 𝐡𝐢𝐠𝐡-𝐯𝐨𝐥𝐮𝐦𝐞 𝐚𝐧𝐝 𝐫𝐞𝐚𝐥-𝐭𝐢𝐦𝐞 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬. 𝐃𝐞𝐞𝐩 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 🏴󠁣󠁬󠁡󠁩󠁿 𝐀𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐍𝐞𝐮𝐫𝐚𝐥 𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐬 — 𝐃𝐞𝐬𝐢𝐠𝐧𝐢𝐧𝐠 𝐚𝐧𝐝 𝐝𝐞𝐩𝐥𝐨𝐲𝐢𝐧𝐠 𝐂𝐍𝐍𝐬, 𝐑𝐍𝐍𝐬, 𝐋𝐒𝐓𝐌𝐬, 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐞𝐫𝐬, 𝐚𝐧𝐝 𝐕𝐢𝐬𝐢𝐨𝐧/𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐦𝐨𝐝𝐞𝐥𝐬 𝐟𝐨𝐫 𝐫𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬. 🏴󠁣󠁬󠁡󠁩󠁿 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧 & 𝐍𝐋𝐏 — 𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 𝐟𝐨𝐫 𝐢𝐦𝐚𝐠𝐞 𝐜𝐥𝐚𝐬𝐬𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧, 𝐨𝐛𝐣𝐞𝐜𝐭 𝐝𝐞𝐭𝐞𝐜𝐭𝐢𝐨𝐧, 𝐬𝐞𝐠𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧, 𝐭𝐞𝐱𝐭 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧, 𝐬𝐞𝐧𝐭𝐢𝐦𝐞𝐧𝐭 𝐚𝐧𝐚𝐥𝐲𝐬𝐢𝐬, 𝐚𝐧𝐝 𝐋𝐋𝐌 𝐢𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧. 𝐋𝐋𝐌 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐞𝐫-𝐁𝐚𝐬𝐞𝐝 𝐌𝐨𝐝𝐞𝐥𝐬 — 𝐄𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞 𝐢𝐧 𝐆𝐏𝐓, 𝐋𝐋𝐚𝐌𝐀, 𝐁𝐄𝐑𝐓, 𝐚𝐧𝐝 𝐨𝐭𝐡𝐞𝐫 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐞𝐫 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞𝐬, 𝐢𝐧𝐜𝐥𝐮𝐝𝐢𝐧𝐠 𝐞𝐧𝐜𝐨𝐝𝐞𝐫, 𝐝𝐞𝐜𝐨𝐝𝐞𝐫, 𝐚𝐧𝐝 𝐞𝐧𝐜𝐨𝐝𝐞𝐫-𝐝𝐞𝐜𝐨𝐝𝐞𝐫 :

AI models are only as good as the human feedback behind them. A response can look convincing and still contain factual errors, poor reasoning, inconsistent labels, or subtle quality issues that affect the final model. That’s where I come in. I work with AI teams to evaluate, annotate, review, and improve training data. My experience spans LLM evaluation, quality auditing, image and video annotation, multimodal data, response evaluation, and detailed QA work where consistency and guideline adherence matter. I don’t just complete tasks quickly. I pay attention to the edge cases—the ambiguous annotation, the hallucinated claim, the inconsistent label, the poorly grounded caption, or the model response that sounds right but fails the rubric. What I can help you with: • AI/LLM Evaluation – response scoring, ranking, factuality, relevance, reasoning, hallucination detection, and rubric-based evaluation • Data Annotation – image, video, text, document, and multimodal annotation • Quality Assurance – reviewing annotations, identifying inconsistencies, correcting errors, and maintaining dataset quality • Image & Video Annotation – bounding boxes, classification, captioning, object identification, and detailed visual evaluation • AI Training Data – creating, reviewing, and refining high-quality human feedback for machine learning systems • Data & Technical Tasks – Python, SQL, structured data review, and related analytical work I’m comfortable working with detailed guidelines, large task volumes, evolving rubrics, and projects where accuracy needs to remain consistent from the first task to the last. If you need someone who can look beyond “good enough,” catch the details others miss, and deliver reliable human judgment for your AI project, let’s talk.

Most AI projects don't fail because the model is weak. They fail because the pipeline leaks, retrieval returns the wrong chunk, or the demo never survives contact with production. I build the unglamorous parts properly so the impressive parts keep working. I'm an AI/ML Engineer specializing in Large Language Models, Retrieval-Augmented Generation, prompt engineering, and MLOps — with deep roots in Computer Vision and NLP. I've shipped RAG systems over messy real-world document sets, fine-tuned and deployed deep learning models for image and gesture recognition, and built LLM agents that run business workflows unattended. WHAT I BUILD ✅ LLM Applications & RAG Systems Document Q&A, internal knowledge assistants, semantic search, and chatbots grounded in your own data. Chunking strategy, embeddings, hybrid search, re-ranking, citations, and hallucination control - tuned until answers are accurate and traceable back to a source. ✅ AI Agents & Workflow Automation Multi-step agents that read email, extract structured data, call APIs, update your CRM, and escalate to a human when confidence drops. Built with LangChain, LangGraph, n8n, Copilot Studio, Power Automate, and MCP tooling. ✅ Prompt Engineering & Evaluation System prompts, few-shot design, structured JSON outputs, function/tool calling, guardrails, and evaluation harnesses so quality is measured instead of guessed. Token and cost optimization included - I've cut inference bills by more than half without losing output quality. ✅ Computer Vision & Deep Learning Image classification, object detection, OCR pipelines, and gesture/pose recognition using EfficientNetB4, ResNet50, YOLO, MediaPipe, and OpenCV. Transfer learning, augmentation, class-imbalance handling, and honest accuracy reporting - including when the data isn't good enough yet. ✅ NLP & Text Intelligence Classification, named entity recognition, summarization, sentiment analysis, topic modeling, and transformer fine-tuning with Hugging Face. Multilingual and domain-specific corpora included. ✅ MLOps & Deployment FastAPI services, Dockerized inference, CI/CD, model versioning, monitoring, drift detection, and deployment on AWS, Azure, or GCP. Your model runs on a server with logs and alerts, not in a notebook on someone's laptop. ✅TECH STACK Languages & ML: Python, PyTorch, TensorFlow, Keras, Scikit-learn, SQL, Node.js LLMs: OpenAI GPT, Anthropic Claude, Gemini, Llama, Mistral, open-source models Frameworks: LangChain, LangGraph, LlamaIndex, Hugging Face Transformers, MCP Vector DBs: Pinecone, Weaviate, Qdrant, ChromaDB, FAISS, pgvector Vision: OpenCV, MediaPipe, YOLO, EfficientNet, ResNet, Detectron2 Serving: FastAPI, Flask, Streamlit, Gradio, Next.js MLOps: Docker, GitHub Actions, MLflow, Weights & Biases, Airflow Cloud: AWS (SageMaker, Lambda, S3), Azure AI, Google Vertex AI Data: Pandas, NumPy, PostgreSQL, MongoDB, ETL pipelines, web scraping Automation: n8n, Zapier, Power Automate, Copilot Studio ✅HOW I WORK 1) Outcome first. Before writing code, I want to know what decision or task the AI is supposed to improve and how we'll both know it worked. 2) Prototype fast. A working slice in days, not a specification document in weeks. 3) Measure honestly. Accuracy, latency, cost per request, and failure modes. If retrieval is only hitting 70%, you'll hear it from me before you find it yourself. 4) Ship and hand over. Clean code, documentation, and a walkthrough so your team isn't permanently dependent on me. ✅WHAT YOU GET WORKING WITH ME - Plain-English communication - no jargon smokescreen, no vague status updates - Realistic timelines, and an early warning the moment something slips - Daily or milestone-based updates, whichever suits your team - Code you fully own, documented and reproducible - Overlap with US, EU, and APAC business hours - NDA and IP assignment signed before work starts, on request - Post-delivery support so the system keeps running after handover GOOD FITS Startups that need an AI feature built end to end. Teams sitting on a pile of PDFs, tickets, contracts, or call transcripts they want to query in natural language. Businesses buried in manual data entry and repetitive review work. Companies with a proof-of-concept that now has to become a real product. Founders who want an honest technical opinion on whether AI is even the right tool for the job. PROBABLY NOT A FIT Projects expecting 99% accuracy from 40 training images, or a brief that says "build me an AI" with no defined problem behind it. I'd rather tell you that in the first message than spend your budget discovering it in week three. Whether it's a two-day prompt optimization, a RAG system that has to be right the first time, or a three-month platform build, message me with what you're trying to achieve. I'll tell you honestly whether I'm the right person for it, roughly what it should cost, and how I'd approach the first milestone. Let's turn your idea into a system that actually runs in production.

I am an AI Data Annotation Expert specializing in creating high-quality training datasets for Artificial Intelligence, Machine Learning, Generative AI, Large Language Models (LLMs), Computer Vision, and Natural Language Processing (NLP) projects. I help AI companies, startups, and research teams improve their models through accurate data labeling, annotation, validation, and AI model evaluation. With strong attention to detail and experience following complex annotation guidelines, I deliver reliable, consistent, and high-quality datasets that help machine learning models perform better. My AI Data Annotation Expertise: 🧠 LLM & Generative AI Data Services * LLM response evaluation * AI chatbot testing * Prompt-response ranking * Human feedback annotation * RLHF (Reinforcement Learning from Human Feedback) * AI output quality assessment * Factuality and relevance checking * AI safety evaluation * Prompt evaluation * Instruction-following evaluation 📝 Text Annotation & NLP * Text classification * Sentiment analysis * Intent classification * Named Entity Recognition (NER) * Entity extraction * Text categorization * Search relevance evaluation * Content moderation * Language data annotation * Document annotation * Conversation annotation 👁️ Image & Computer Vision Annotation * Image classification * Object detection * Bounding box annotation * Polygon annotation * Semantic segmentation * Instance segmentation * Keypoint annotation * Landmark annotation * OCR annotation * Medical/technical image labeling * Autonomous vehicle dataset annotation 🎥 Video & Audio Annotation * Video object tracking * Action recognition * Event tagging * Frame-by-frame annotation * Speech transcription * Audio classification * Speaker identification * Audio quality evaluation Annotation Tools & Platforms I Work With: * Labelbox * CVAT (Computer Vision Annotation Tool) * Label Studio * Doccano * Prodigy * Supervisely * V7 Darwin * Roboflow * Scale AI * Appen * TELUS International AI Platforms * Toloka * Amazon SageMaker Ground Truth * Google Cloud Data Labeling * Azure Machine Learning Data Labeling * RectLabel * LabelImg * VIA (VGG Image Annotator) * MakeSense.ai * FiftyOne * Snorkel * LightTag * UBIAI * Datasaur * INCEpTION I can also quickly adapt to custom annotation platforms and client-specific workflows. Quality Assurance & Data Validation I focus on delivering production-ready datasets through: ✔ Annotation accuracy checks ✔ Guideline compliance ✔ Data consistency review ✔ Error identification and correction ✔ Quality control processes ✔ Dataset validation ✔ Detailed feedback reporting Why Clients Choose Me: ✅ Strong attention to detail ✅ Ability to handle large-scale annotation projects ✅ Fast understanding of annotation guidelines ✅ Consistent labeling quality ✅ Experience with AI/ML workflows ✅ Reliable communication and deadline commitment I support projects related to: * Artificial Intelligence (AI) * Machine Learning (ML) * Deep Learning * Generative AI * Large Language Models (LLMs) * Computer Vision * Natural Language Processing (NLP) * Autonomous Systems * AI Chatbots * Data Quality Improvement If you need accurate, scalable, and reliable AI training data, I can help you build better AI models with high-quality human-verified datasets.