Vladimir Rotaru

Senior Machine Learning Engineer | Data Scientist

Eleks

Dec 2023 - Current (2 years 7 months)

Led the full delivery of AI/ML systems across healthcare projects, driving solution design, stakeholder alignment, and architecture decisions in cross-functional teams. Worked on projects involving document intelligence and medical image processing using deep learning and generative Al. Defined Al engineering best practices and contributed to strategic decisions on infrastructure, model lifecycle, and ethical Al standards across client portfolios. Designed and implemented deep learning models using PyTorch 2.1 and TensorFlow 2.14 to support document classification and image recognition tasks within healthcare platforms. Developed scalable inference services using FastAPI 0.110 and deployed them with Docker and Kubernetes 1.29, ensuring stab

Senior Machine Learning Engineer

Scale Tech

Oct 2022 - Sep 2023 (1 year)

Applied machine learning in the finance domain, focusing on credit risk modeling, fraud detection, and real-time customer engagement tools. Contributed to building ML infrastructure aligned with compliance requirements in financial services across EU markets. Built production-ready ML pipelines for credit scoring and network optimization using XGBoost, scikit-learn 1.3 and domain-specific feature engineering. Deployed containerized ML APIs using Flask 2.3 and Gunicorn 21, integrated with Redis 7 and PostgreSQL 15 for fast transactional model inference. Developed job orchestration workflows using Apache Airflow 2.8 to manage model training and prediction pipelines at scale. Applied Explainable Al techniques using SHAP and LIME to ensure inte

AI/ML Developer

Scale Tech

Jan 2021 - Sep 2022 (1 year 9 months)

Supported Al adoption in e-commerce and retail by building models for inventory forecasting, dynamic pricing, and process optimization. Contributed to integrating Al into supply chain workflows, with emphasis on scalability and modular design. Developed ML models for demand forecasting and pricing optimization using LightGBM and NeuralProphet, customized for high-volume retail data. Created modular training and evaluation scripts using custom scikit-learn 1.2 pipelines with hyperparameter tuning supported by Optuna. Built data preparation and validation workflows in dbt and Snowflake ensuring consistent input for model training. Packaged and deployed inference services using Docker and managed deployment with AWS ECS and Fargate in a cloud-

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Python Developer

REI Development Services

Apr 2018 - Dec 2020 (2 years 9 months)

Joined the company as an intern, contributing to backend automation scripts and internal tooling while learning production-grade Python development. Promoted to full-time developer, working on backend systems powering real estate and logistics platforms, with a focus on reliability and modular design. Designed and implemented backend services using Django 3.2 and Django REST Framework for logistics management and tracking tools. Developed data ingestion and transformation pipelines using Apache Airflow 2.x to integrate third-party APIs and internal ERP systems. Contributed to an internal recommendation engine prototype, supporting data preparation and experimentation in Jupyter using scikit-learn and Pandas. Refactored legacy monolithic Pyt

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