Dingu Sagar
Software Engineer Intern at Amazon
Austin, Texas, United States
Summary
🤩
Rockstar🎓
Top SchoolDingu Sagar is an AI/ML-focused software engineer with nine years of experience building production-grade deep learning and MLOps systems, now based in Austin and currently at Apple. He has delivered measurable impact across healthcare, retail, and video analytics—boosting medical coding accuracy from 70% to 94%, driving a 16% improvement in a key business metric, and detecting inventory anomalies worth millions at Amazon. Comfortable across the stack, Dingu has migrated legacy NLP pipelines to LLM- and RAG-based services, optimized models for low-latency deployment with ONNX/quantization, and led 3D CNN and transformer experiments for action recognition. He contributes to open-source tooling, notably improving logging robustness in the popular Rasa SDK to aid developer observability. Trained at Georgia Tech (MS in Machine Learning) and with a background in both research and product-first engineering, he blends rigorous experimentation with pragmatic productionization.
9 years of coding experience
3 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at Georgia Institute of TechnologyKendriya Vidyalaya SangathanComputer Engineering (BTech + MTech) 5 Year Program Computer Engineering, Computer Engineering (BTech + MTech) 5 Year Program Computer Engineering at Indian Institute of Information Technology Design & Manufacturing Kancheepuram
Stackoverflow
68reputation
11kreached
1answer
3questions
Github Skills (14)
argparse10
logging10
ras10
sdk10
python10
application-design8
graph6
command-line-arguments6
keyword-argument6
gunicorn6
adjacency-list6
fastapi6
adjacency-matrix6
gil6
Programming languages (7)
Github contributions (5)
RasaHQ/rasa-sdk
Oct 2020 - Jan 2021
SDK for the development of custom actions for Rasa
Role in this project:
Back-end Developer
Back-end DeveloperContributions:14 commits, 3 PRs, 8 comments in 2 months
Contributions summary:Dingu focused on enhancing the logging functionality within the Rasa SDK. They implemented methods to configure file logging, added arguments for specifying log files, and integrated these configurations into the main application and the action endpoint. Furthermore, the user refactored existing logging-related code, including renaming methods, adding module names to log formatters, and adjusting log levels for improved debugging and monitoring. These changes provided developers with more control over logging behavior.
custom-actionspythonrasasdk
dingusagar/AsyncFaceRecognition
Apr 2020 - Jan 2023
A demo python application for face recognition based attendance system using enhancement of low resolution images by super resolution deep learning models.
Contributions:21 commits, 4 PRs, 4 pushes in 2 years 9 months
pythonenhancementdeep-learningface-recognitionrecognition
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