Machine Learning Engineer - Python / Production ML

Описание вакансии

🔥 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