Position: NLP Engineer
Category: Data Science
English level: fluent
Years of experience: 3


•	Deployed a high-load BERT-based microservice for an outbound voice bot that classies client intent, replacing 700 call centre managers and handling nearly 5 million calls per month.
•	Conducted an A/B test comparing the Rasa DIETClassier to a BERT, demonstrating that the BERT-based classier made a 7 percentage point reduction in errors from overall calls.
•	Fine-tuned a Large Language Model (LLama 2) using PEFT to generate personalized scripts for the voice bot, fostering more diverse and client-specific conversations compared to the previous one-size-fits-all script approach.
•	Optimized models to enhance production efficiency, utilizing tools such as JMeter for resource identification and implementing Python's lru_cache library for effective caching. Further enhanced the performance of LLMs by employing 8-bit quantization, significantly streamlining production operations.
•	Developed a Catboost model to monitor the performance of the voice bot, reducing the error response time from 24 hours to 1 hour.
•	Constructed a BERT model that identies rude behaviour from managers towards customers, leading to a 58% reduction in customer complaints within 6 months.