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Описание вакансии
TL;DR
Machine Learning Engineer (Production ML) (Python/Fintech): Turning research-stage machine learning models into reliable production-grade systems with an accent on model serving, monitoring, retraining, and data pipelines. Focus on deploying scalable ML services, detecting model drift, engineering features from financial datasets, and maintaining robust production APIs and infrastructure.
🔥 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
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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