Senior Machine Learning Engineer
# Senior Machine Learning Engineer **Globaldev Group** · Ukraine · `Remote` · `Full Time` 💼 **Уровень роли:** `Senior` 🕒 **Статус:** *Опубликовано: сегодня* · *Источник: Himalayas (JSON API)* --- ### Top Skills & Match 🎯 **Ключевой стек роли:** `[MLOps-Engineer]` `[Data-Science]` `[Senior-Staff-Machine-Learning-Engineer]` `[Senior-AI-ML-Engineer]` `[Senior-ML-Engineering]` `[Sr.-Staff-Machine-Learning-Engineer]` `[Senior-Machine-Learning-Data-Scientist]` `[Senior-Machine-Learning-Scientist]` `[Senior-Data-Science-Engineer]` `[Lead-Machine-Learning-Engineer]` `[Machine-Learning-Engineer]` `[Machine-Learning]` `[Senior-ML-Engineer]` --- ### About the Role We are looking for a Senior Machine Learning Engineer to design, own, and scale predictive systems that power VIS.X - programmatic advertising platform. You will take end-to-end responsibility for high-impact ML initiatives (e.g., pricing optimization, bid prediction, performance forecasting, delivery optimization) and translate complex business problems into robust, production-grade machine learning systems. This is a senior individual contributor role with leadership potential. You will help shape our ML architecture, standards, and long-term AI strategy, with the opportunity to grow into a team lead role as we expand our data science capabilities. Requirements: 5+ years of experience in machine learning / applied ML roles with production ownership Proven track record of deploying and maintaining ML systems in real-world environments Strong Python skills (e.g., pandas, scikit-learn, PyTorch/TensorFlow) Solid knowledge of statistics, experimentation design, and model evaluation Experience working with large-scale datasets and performance-critical systems Understanding of MLOps principles (model lifecycle, monitoring, CI/CD integration, retraining pipelines) Strong problem ownership mindset - ability to independently structure ambiguous challenges Ability to translate business trade-offs into modeling decisions Experience in AdTech, marketplaces, or auction-based systems is a plus Experience working in high-scale, real-time systems is a plus Responsibilities: Take ownership of machine learning problems from concept to production Design, build, and deploy predictive models (e.g. pricing, bidding, optimization, forecasting) Develop scalable feature engineering and data pipelines for large-scale datasets Define experimentation frameworks (A/B testing, offline validation, model comparison) Ensure production-grade MLOps: monitoring, retraining, drift detection, reliability Collaborate closely with DevOps, Product, Engineering teams to align ML with business impact Quantify model impact on revenue, margin, and performance KPIs Contribute to building our long-term ML architecture and best practices What we offer: Comfortable environment, challenging tasks and a long-term interesting project; Covered 20 days of vacation; Working with top notch equipment; Bookkeeping by a professional accountant; Help and support from our caring HR-team; Originally posted on Himalayas
- MLOps-Engineer
- Data-Science
- Senior-Staff-Machine-Learning-Engineer
- Senior-AI-ML-Engineer
- Senior-ML-Engineering
- Sr.-Staff-Machine-Learning-Engineer
- Senior-Machine-Learning-Data-Scientist
- Senior-Machine-Learning-Scientist
- Senior-Data-Science-Engineer
- Lead-Machine-Learning-Engineer
- Machine-Learning-Engineer
- Machine-Learning
- Senior-ML-Engineer
Наблюдалась 2026-09-17, впервые 2026-09-17, источник — Himalayas (JSON API).