Mariia Rodina

Angestellt, Machine Learning Engineer, Epoch8
Yerevan, Armenia

Skills

Machine Learning
Data Science
Python
Python pandas
scikit-learn
PyTorch
LLM
Natural Language Processing (NLP)
Recommendation Systems
SQL
Java
Software Development
Team work
Deep Learning
Chatbot
ChatGPT
Artificial intelligence
ML
NumPy
Neural Networks
Computer Science
neo4j
Git
Docker
Kubernetes
Graph Database
Leadership
Communication skills

Timeline

Professional experience for Mariia Rodina

  • Current 3 years and 4 months, since Jan 2023

    Machine Learning Engineer

    Epoch8

    * Designed and applied an external FAQ service that ensured the delivery of new data to the chatbot within 15 minutes, with the top three bot responses achieving over 90% accuracy during validation; * Leveraged a text communication channel as a data source to develop an AI-based text assistant for searching a formalized data source with a response speed of 2-5 ms; * Mentored junior team members, providing guidance on best practices, coding techniques, and machine learning model development;

  • 9 months, May 2022 - Jan 2023

    Machine Learning Engineer

    Smart Consulting

    * Pioneered the automation of graph database population and semantic search, dramatically reducing the amount of man hours required for data labelling. This approach resulted in several-fold savings in time and resources, significantly boosting overall productivity. * Utilized cutting-edge techniques in NLP, such as metric learning on texts, topic modeling, and entity extraction, employing pre-trained, fine-tuned, or trained from scratch models.

  • 3 years, Jun 2019 - May 2022

    Machine Learning Engineer

    CJSC ”NeoCor”

    * Designed and developed the warehouse demand forecaster, that reduced redundant warehouse processes by 1.8 times. * Designed and developed the multitasked service supporting a sales department with the zero-shot contract predictor and the tender’s proposal system (partial implementations) in it. * Collected a dataset with a million+ of records from lightly structured sources (web scraping, Selenium + BeautifulSoup libs). Labeled data with an active learning algorithm.

Languages

  • English

    C1 (Fluent)

  • Russian

    C2 (Expert / native speaker)

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