Machine Learning Engineer - Python / Production ML

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Описание

🔥 Machine Learning Engineer - Python / Production ML Elinext is an international software development company with 25+ years of experience, helping clients worldwide build and scale reliable digital products. We work across Fintech, Healthcare, Manufacturing, AI/ML, Cloud, Enterprise Software, and other domains. We are currently looking for an experienced Machine Learning Engineer to join an international project in the financial domain. 📍 Location: Poland, Georgia, Uzbekistan, Kazakhstan, Armenia and other eligible locations 🏠 Format: Remote 🗣 Customer interview: Yes 📝 Test task: No About the role The main focus is on taking machine learning models beyond the research stage and turning them into reliable production-grade systems. You will work with real financial datasets, deploy and maintain ML services, monitor model performance, improve data pipelines, and collaborate closely with software engineers and data scientists. Responsibilities — Develop, deploy, and maintain machine learning models and services — Keep existing ML solutions performant, stable, and robust — Turn research prototypes into production-grade ML systems — Harden code, add tests, logging, monitoring, and observability — Own model serving, deployment, scaling, and lifecycle management — Monitor model performance and detect drift — Build and maintain retraining processes — Engineer and evaluate features on real financial datasets — Calibrate and validate models to ensure reliable behavior — Build and improve data pipelines — Collaborate with software engineers and data scientists — Document approaches, experiments, and architecture decisions MUST HAVE — Strong software engineering skills in Python — Clean, typed, maintainable, and well-tested code — Experience with version control and CI/CD — Strong knowledge of NumPy, Pandas, scikit-learn, PyTorch — Solid understanding of machine learning, statistics, and model evaluation — Proven experience taking ML models into production — Experience with model serving, monitoring, drift detection, and retraining — Experience building production APIs and services with FastAPI, Flask, or similar — Experience with Docker / containerization — Experience deploying services on Kubernetes or similar environments — Strong feature engineering experience with structured / tabular data — Experience working with large datasets and reliable data pipelines — Strong communication skills with technical and business stakeholders Nice to Have — Financial / fintech project experience — Experience with production MLOps practices — Experience with highly scalable ML platforms — Experience with model explainability and reproducibility — Experience with distributed data processing or cloud environments 💚 What We Offer — Small-company feel within a fast-growing international environment — Friendly, collaborative, and mission-driven team — 25 calendar days of vacation + 5 additional paid sick days — Medical insurance — Corporate English courses — Corporate events and team-building activities — Support with professional certifications — Reimbursement for professional courses and training — Long-term international projects — Opportunities for professional and technical growth

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