Rahul K B

Resume

Staff Machine Learning Engineer & TLM at Coinbase

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Summary

Staff Machine Learning Engineer driving AI-powered automation and security to transform customer experience. I lead innovations in LLM-driven chat, search, fraud detection, and agent assistance, building scalable systems that enhance efficiency, personalization, and trust. Passionate about leading high-impact teams and bridging the gap between research and production.

Experience

Staff Machine Learning Engineer & TLM

Nov 2021 – Present
Coinbase
  • LLM-Powered Automation: Architected scalable systems transforming agent efficiency and customer self-service.
  • Bad Actor Guardrails: Developed a system detecting agent solicitations with >99% precision using LLMs ($XXM impact).
  • Coinbase Chatbot: Built the first in-house LLM chatbot automating ~50% of chat contacts ($XXM impact).
  • Agent Assist: Designed reactive and proactive recommendations to support agents ($XM impact).
  • Help Center Search: Built LLM-powered search improving relevance and precision ($XXXK impact).

Founding/Lead Machine Learning Scientist

June 2018 – Nov 2021
Agara (Acquired by Coinbase)
  • Pioneered AI-driven voice automation and real-time conversation intelligence.
  • Voice Assist: Implemented LSTM/BERT models for real-time agent assistance.
  • Voice Auto: Created state-of-the-art transformer TTS models for autonomous agents.

Computer Scientist

July 2017 – June 2018
Sigtuple
  • Developed Aadi, a computer vision-based analyzer for andrology using Deep Learning (UNet, ResNets).
  • Solved multi-object tracking problems for medical imaging analysis.

Research Experience

Research Assistant

Feb 2017 – June 2017
Carnegie Mellon University (Music Technology Group)
  • Developed FLOCTRL, a platform for the Laptop Orchestra using Forward Synchronous Time-map.
  • Established discovery protocols for dynamic device identity and algorithmic music composition.

Research Assistant

May 2016 – July 2016
IIT Gandhinagar (Audio Forensics Lab)
  • Implemented automatic cellphone detection algorithms using high-frequency audio feature analysis.
  • Developed stochastic feature-based learning models for device recognition.

Patents

Education

Master of Computer Science

2023
University of Illinois Urbana-Champaign
GPA: 3.91

B.Tech, Electrical and Electronics Engineering

2017
National Institute of Technology, Karnataka
CGPA: 8.6

Contact

Skills

PyTorchTensorFlowLLMsGenAIAWSGCPFlinkSparkAirflowGit