Position: Machine Learning Engineer
Category: Data Science
English level: upper
Years of experience: 3

- Successfully delivered all the projects.
- Published article on kdnuggets
- Successful presentations on international conferences such as Photonics WEST (USA), IONS Yerevan (Armenia)
- Preprocessing and cleaning large datasets to prepare them for multi-label classification problem, for NER problem, for Retrieval Augmented Generation problem;
- Evaluating and selecting appropriate ML techniques and models such as transformers with different losses;
- Training, fine-tuning, and validating ML models;
- Optimizing and deploying ML models to production environments;
- Building retraining pipeline for the final model;
- Explaining and interpreting model outputs and results to non-- technical stakeholders;
- Preparing the report and writing the article for publication.
- Prompt Engineering for the LLMs on Question-Answering task;
-Conducting A/B testing and experimentation to evaluate and compare different ML models or algorithms;
- Building step function pipeline;
- Released the framework that understands the accuracy of predicted measurements, sizes and 3d avatars;
- Worked closely with US actual data from scanners. Designed algorithms to track and detect anomalies in multiply data, which allowed tracked about 85% of unhealthy data;
- Implemented model versioning and deployment strategies to manage the lifecycle of ML models;
- Developed the monitoring system for a whole pipeline.
- Designed a model in pilot to increase marketing resources for more than 6 large USA brands;
- As a part of Data Engineering jobs setup correct ETL processes with Amazon EMR. This helped client to economy more than 40 % in money terms and gave the win in time processing more than 10x;

Solutions: NLP ( Multi-Label text classification, NER with SOTA FLAIR approaches, Document Q&A System using Langchain / OpenAI) , CV ( Object classification (YOLOv8)), classical ML ( Regression Task, Clusterization Task)

Technologies: Python, AWS (Sagemaker, Step Functions, ECR, S3), Weight and Biases,
Data Version Control, HuggingFace (transformers), FLAIR, Spacy, PyTorch, OpenAI, Docker,  LangChain, Vector Stores (FAISS, Chroma)
- Opportunity of professional growth;
- Flexible schedule