Amogh Mannekote
Bellevue, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolAmogh Mannekote is an applied scientist and NLP researcher with 11 years of experience building and evaluating dialogue systems, semantic parsers, and conversational AI for industry leaders including Amazon and Rasa. He blends research and product sensibilities—designing LLM-based synthetic data and evaluation frameworks that accelerated releases and improved robustness in task-oriented dialogue. An active open-source contributor and documentation specialist on the widely used Rasa project, he focuses on making complex ML tooling more accessible to developers. Based in Bellevue, WA, Amogh is pursuing a PhD in Computer Science while continuing to ship practical ML solutions and HCI-informed interfaces for education and conversational agents.
11 years of coding experience
2 years of employment as a software developer
MES Kishore Kendra Public SchoolBachelor of Engineering (B.E.), Computer Science, Bachelor of Engineering (B.E.), Computer Science at M.S. Ramaiah Institute Of TechnologyDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Florida
English, Kannada, Hindi, Telugu
Stackoverflow
147reputation
93kreached
9answers
8questions
Github Skills (16)
markdown10
markdown-it10
rasa10
documentation10
api-documentation9
yaml8
chatbot6
pytorch6
ajax6
named-entity-extraction6
rasa-core6
html6
rasa-nlu6
php6
android6
Programming languages (4)
Github contributions (5)
RasaHQ/rasa
Feb 2018 - Oct 2019
💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants
Role in this project:
Technical Writer & Documentation Specialist
Technical Writer & Documentation SpecialistContributions:233 commits, 58 PRs, 244 pushes in 1 year 8 months
Contributions summary:Amogh primarily focused on updating and improving the documentation for the Rasa framework. Their contributions included fixing documentation issues, adding missing imports and docstrings, updating meta descriptions, and changing the training data format. They also revamped the stories page and added documentation for auto_fill functionality within slots, demonstrating a focus on improving clarity and user experience.
nlupythonbotspeech-recognitionbotkit
msamogh/rasa-frames
Apr 2020 - Apr 2020
Rasa + Microsoft Frames
Contributions:66 commits, 61 pushes, 1 branch in 12 days
pythonrasamachine-learningtensorflowmicrosoft
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