Machine Learning Engineer - Senior
FinteqHubOverview:
FinteqHub continues to expand the team and is looking for a Machine Learning Engineer. We need a hands-on specialist who will help us build and scale intelligent solutions for payment optimization.
This will be the first ML Engineer in the team, giving you the opportunity to shape ML practices, influence technical decisions, and build solutions from the ground up in a fast-growing fintech product.
About Product:
Finteqhub
А PCI DSS certified payment gateway for online businesses, providing integration with payment systems via a single software platform.
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Purpose of the role:
To design, develop, and deploy machine learning models that improve payment performance and reliability, while laying the foundation for ML direction within the product.
The role focuses on optimizing transaction flows, detecting fraudulent activity, and enabling data-driven decision-making. You will contribute directly to increasing conversion rates, reducing declines and fraud risks, and improving overall efficiency of payment operations through intelligent automation and scalable ML solutions..
Key responsibilities:
Develop, train, and deploy machine learning models to support and optimize payment operations
Work closely with a Product Analyst to translate business requirements into ML solutions
Build and improve models for transaction scoring, anomaly detection, fraud detection, and payment routing optimization
Automate decision-making processes using machine learning approaches
Prepare and process data, including feature engineering and building data pipelines
Monitor model performance and continuously improve model quality and reliability
Participate in the design and development of ML solution architecture
Required Experience:
3+ years of experience in Machine Learning
Strong proficiency in Python and ML libraries (scikit-learn, TensorFlow, PyTorch, etc.)
Experience building and deploying models to production
Solid understanding of statistics and data analysis methods
Experience working with SQL and large-scale data processing
Knowledge of A/B testing principles
Ability to work with business requirements and translate them into ML tasks
Nice to have:
Experience with payment systems or fintech products
Experience developing anti-fraud systems
Knowledge of MLOps (CI/CD for models, monitoring, deployment)
Experience working with streaming data (e.g., Kafka)
Our Benefits:
Full-time work opportunities
Private insurance
An additional Day Off (1) per calendar year
Sports program compensation
Comprehensive Mental Health Programme
Free online English lessons with native speakers
Generous referral program
Training, internal workshops, and participation in international professional conferences and corporate events