Ihar Nestsiarenia's home page

🤵 Personal Information



📊 Summary

Experienced machine learning engineer with over 8 years of industry experience, specializing in NLP and related technologies. Proven track record of successfully leading and delivering ML projects from R&D to production. Skilled in transitioning models from research to production, building search systems, and improving relevancy. Strong expertise in MLOps, with proficiency in AWS Sagemaker, DVC, MLFlow, and AI architecture. Currently seeking Tech Lead positions.

🔨 Working Experience

2021 — now: Lead Machine Learning Engineer / MLOps (EPAM Systems)

Summary: Responsible for utilizing AI to address challenges faced by legal professionals, including designing and implementing search algorithms, developing metrics, establishing pipelines, and automating tasks. Integrated SageMaker, streamlined development process with pipelines, and improved delivery with MLOps practices.

Technologies: Tensorflow, Keras, scikit-learn, spaCy, BM25, word2vec, Solr, DVC, Sagemaker, Python, Docker

2020 — 2021: Lead Machine Learning Engineer / AI Architect (EPAM Systems)

Summary: Played a crucial role in designing and implementing document processing services for a case-management system for lawyers. Conducted R&D, prototyping, and implemented machine learning models and metrics to ensure accuracy and performance.

Technologies: flair, spacy, huggingfaces, nlpaug, sklearn, flask, python, docker, pytorch, AWS Step Functions, AWS SQS, git, DVC, s3, scrum, kanban, jira, tesseract, ABBYY finereader, elasticsearch

2019 — 2020: Lead Machine Learning Engineer / Search Engineer (EPAM Systems)

Summary: Worked on ML algorithms, ETL pipelines, model deployment, and result analysis for a legal tech product targeting EU markets. Collaborated with business stakeholders to implement ranking algorithms, language models, and various NLP models.

Technologies: flask, python, java, docker, AWS, TensorFlow projector, MLFlow, git, jira, solr, keras, stanfordnlp, gensim, sklearn, word2vec, BPE embeddings, fasttext, solr, elasticsearch

2018 — 2019: Senior Machine Learning Engineer at R&D Team (EPAM Systems)

Summary: Involved in AI-related projects and POCs, including deep learning, topic modeling, document classification, and knowledge management. Responsible for deploying and integrating models in production.

Technologies: Tensorflow, Keras, scikit-learn, bigARTM, NLTK, spaCy, Fasttext, BM25, word2vec, gensim, Matplotlib, Jupyter Notebook, Node.js, Java, XSLT, and Elasticsearch

2016 — 2018: Senior Software Engineer / Data Engineer (EPAM Systems)

Summary: Assisted in the migration of a backend research platform for lawyers, focusing on improving accessibility and searchability. Responsible for batch processing of content and metadata, as well as delivering content to the search engine.

Technologies: Elasticsearch, graph databases, Semantic Web, RDF/OWL, SPARQL Jena-TDB, JBoss Fuse, Tomcat, Apache Fuseki, ELK, Kibana, Sonar, FindBugs, PMD, Checkstyle, Winscp, Bamboo CI, Git, JIRA, Maven, Ant, Linux, Cron, Java 7, Java EE, ActiveMQ, Spring 3, REST, SOAP, Tomcat, JBoss Fuse, Jena, XSLT, RDF, XML, XPath, Semantic Web, JUnit, Cucumber, Camel, Blueprint, Log4J, Lombok.

🧑🏻‍🏫 2018 — 2019: Senior Teacher of Information Technologies Department — GSTU by P. Sukhoi

🧑🏻‍🏫 2015 — 2016: Senior Instructor (Java) — Educational Center “IT Class”

🧑🏻‍🏫 2014 — 2016: Assistant of Information Technologies Department - GSTU by P. Sukhoi

🎓 Education

🧭 Other activities