Overview:
FinteqHub is growing and we’re looking for a Machine Learning Engineer to join the team. We’re looking for a hands-on specialist who can help us build and scale intelligent solutions for payment optimization.
This will be the first ML role in the team, offering a unique opportunity to shape ML practices, influence technical decisions, and build solutions from the ground up in a fast-growing fintech product.
About Product:
А PCI DSS certified payment gateway for online businesses, providing integration with payment systems via a single software platform.
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.)
- Solid understanding of statistics and data analysis methods
- Experience building and deploying models to production
- 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 remote work opportunities and flexible working hours
- Private insurance
- Additional 1 Day Off per calendar year
- Sports program compensation
- Comprehensive Mental Health Programme
- Free online English lessons with a native speaker
- Generous referral program
- Training, internal workshops, and participation in international professional conferences and corporate events.
Full-time | Fully Remote