Machine Learning Engineer – Senior
SOFTSWISS 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 within our FinteqHub product.
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 environment.
Finteqhub
А PCI DSS certified payment gateway for online businesses, providing integration with payment systems via a single software platform.
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To design, develop, and deploy machine learning models that improve payment performance and reliability within FinteqHub, while laying the foundation for ML direction across 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 the overall efficiency of payment operations through intelligent automation and scalable ML solutions.
- 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
- 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
- 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)
Learn more about our hiring process here (link) – what to expect, how to prepare, and what makes SOFTSWISS different.
