Machine Learning Engineer

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

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;

• Vacation (depends on the location) + 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.