Artjom Jegorov
AI & ML Engineer
Experience
AI & ML Engineer
ElevenLabs
- Built and optimized multilingual TTS and voice cloning models using PyTorch and Hugging Face Transformers, increasing MOS score by 0.7 and improving intelligibility across 3 languages, reducing post-editing time by 25%.
- Engineered prosody modeling pipelines using phoneme-level attention, increasing speech continuity and expressiveness.
- Built FastAPI microservices for real-time TTS, containerized with Docker and scaled via Kubernetes for international deployments.
- Used ONNX Runtime and TensorRT to improve inference speed, cutting latency by up to 40% and making GPU usage more efficient.
- Worked on audio preprocessing and augmentation with Librosa, NumPy, and Hugging Face Datasets, increasing data variety and voice accuracy.
- Used MLflow, Airflow, and GitHub Actions for automated tracking, retraining, and continuous delivery of speech models.
- Collaborated with linguists and audio researchers to improve phonetic alignment and acoustic consistency, supporting ElevenLabs Pro Voice API and real-time dubbing projects.
AI & ML Engineer
Norby AI
- Designed and developed fraud detection, risk assessment, and claims scoring systems using XGBoost, LightGBM and CatBoost, improving decision accuracy and automation.
- Built churn and customer lifetime value (CLV) prediction models with Python, Scikit-learn and Pandas, enabling data-driven retention strategies and risk profiling.
- Integrated Flask and FastAPI APIs into underwriting workflows and automated ETL pipelines with Airflow, SQL and AWS Lambda, processing millions of records daily.
- Implemented MLflow and Jenkins for model tracking, retraining, and deployment, ensuring reproducibility and continuous model improvement.
- Created Prophet and ARIMA-based forecasting tools to predict claims volume, detect anomalies, and improve resource planning accuracy.
- Reduced manual claim reviews by 30% through predictive triage models and supported AI governance and model validation initiatives.
AI Engineer
MindTitan
- Worked on AI-driven web and data systems using Python, TensorFlow, and OpenCV, delivering NLP and computer-vision solutions for telecom and government clients.
- Used FastAPI, Docker, and Kubernetes (AWS EKS) to create and run scalable microservices for model inference and management.
- Automated data ingestion and preprocessing pipelines with BeautifulSoup, Requests, and REST APIs, improving data consistency and training efficiency.
- Optimized Redis caching and PostgreSQL indexing to reduce data access latency, improving chatbot response time and overall analytics performance.
- Conducted AI deployment and MLOps workshops, guiding developers on CI/CD, API integration, and infrastructure management for production ML systems.
NLP Engineer & Speech Engineer
FeelingStream
- Developed AI-driven sentiment analysis and speech processing pipelines using spaCy, Scikit-learn, and Flask to improve understanding of customer feedback.
- Utilized Librosa for audio feature extraction, NLTK for text tokenization, and Pandas for data manipulation in multilingual STT and classification pipelines.
- Improved call-center efficiency and satisfaction by delivering AI insights through topic modeling, acoustic analysis, and dashboard visualizations in Plotly and Tableau.
Backend Python Engineer
Veriff
- Assisted in developing backend components for Veriff’s identity-verification platform using Python, Flask, and Django REST, handling request routing, data validation, and internal API communication.
- Supported senior engineers in maintaining microservices and internal tools using AsyncIO, Pydantic, and SQLAlchemy, contributing to fraud-prevention and identity-verification workflows.
- Integrated backend services with Redis and Celery task queues, wrote unit tests, improved documentation, and participated in debugging and troubleshooting across staging environments.
Summary
AI & ML Engineer with 9+ years of experience designing, training, and deploying production-scale machine learning systems across speech synthesis, insurance, AI consulting, and NLP analytics. Skilled in Python, PyTorch, TensorFlow and FastAPI, with strong expertise in MLOps, cloud infrastructure, multimodal AI and scalable backend integration. Adept at building intelligent applications that transform data into real-world insights and automation.
Skills
Ai & Ml
- Python 3.11–3.12, Pytorch, Tensorflow, Jax, Hugging Face Transformers, Scikit-learn, Xgboost, Lightgbm, Catboost, Cnns, Rnns, Transformers, Llms, Nlp, Speech Synthesis (Tts), Voice Cloning, Prosody Modeling, Arima, Prophet, Lstm, Onnx Runtime, Tensorrt, Opencv, Numpy, Pandas, Scipy, Cupy.
Backend & Apis
- Fastapi, Flask, Django Rest, Graphql, Grpc, Websockets, Celery, Redis Streams, Asyncio, Pydantic, Sqlalchemy, Microservices Architecture.
Data Engineering & Mlops
- Mlflow, Apache Airflow, Apache Spark, Ray, Dask, Docker, Kubernetes (Eks, Gke, Aks), Helm, Jenkins, Github Actions, Gitlab Ci/cd, Model Registry, Etl Pipelines, Dataset Versioning.
Cloud & Databases
- Aws (Ec2, S3, Lambda, Ecr, Sagemaker), Gcp (Vertex Ai, Cloud Run, Bigquery), Azure Ml, Postgresql, Mongodb, Redis, Elasticsearch, Snowflake.
Collaboration
- Streamlit, Plotly, Tableau, Grafana, Git, Agile/scrum.
Languages
Education
Tallinn University of Technology
Bachelor’s degree · Computer Science · Tallinn, Estonia
Profile
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