It's fun to work in a company where people truly BELIEVE in what they're doing!
 

We're committed to bringing passion and customer focus to the business.

About Us

Kyriba is a global leader in liquidity performance that empowers CFOs, Treasurers and IT leaders to connect, protect, forecast and optimize their liquidity. As a secure and scalable SaaS solution, Kyriba brings intelligence and financial automation that enables companies and banks of all sizes to improve their financial performance and increase operational efficiency. Kyriba’s real-time data and AI-empowered tools empower its 3,000 customers worldwide to quantify exposures, project cash and liquidity, and take action to protect balance sheets, income statements and cash flows. Kyriba manages more than 3.5 billion bank transactions and $15 trillion in payments annually and gives customers complete visibility and actionability, so they can optimize and fully harness liquidity across the enterprise and outperform their business strategy. For more information, visit www.kyriba.com.

Position Overview

We are seeking a Software Engineer to integrate and implement standard machine learning models (such as classification, regression, clustering) into our production systems. This role focuses on incorporating pre-trained ML models into our existing applications and data flows, ensuring reliable and efficient implementation.

Key ResponsibilitiesIntegrate pre-trained ML models (scikit-learn, XGBoost, etc.) into production systemsImplement model serving solutions for classification and regression tasksDevelop data preprocessing and transformation pipelinesEnsure efficient model inference in production environmentsBuild monitoring systems for model performance and data driftOptimize model serving for latency and throughputImplement proper error handling and fallback mechanismsCreate documentation for model integration and maintenanceRequired QualificationsBachelor's degree in Computer Science, Software Engineering, or related field3+ years of experience in software developmentStrong programming skillsExperience with ML libraries (scikit-learn, XGBoost, LightGBM)Proficiency in data preprocessing and feature engineeringStrong understanding of RESTful APIs and microservicesExperience with version control (Git) and CI/CD pipelinesKnowledge of SQL and database systemsTechnical SkillsProgramming Languages: Python, JavaML Libraries: scikit-learn, XGBoost, LightGBMModel Serving: Flask, FastAPI, or similarData Processing: pandas, numpyDatabases: SQL, NoSQLVersion Control: GitContainers: DockerCI/CD Tools: Jenkins, GitLab CI, or similarMonitoring Tools: Prometheus, Grafana, or similarPreferred QualificationsExperience with model versioning and deployment toolsKnowledge of feature stores and model registry conceptsUnderstanding of statistical analysis and data validationExperience with distributed computingFamiliarity with A/B testing and experiment trackingExperience with cloud platforms (AWS, Azure, or GCP)Key CompetenciesStrong software engineering practicesUnderstanding of ML model lifecycleData structure and algorithm expertisePerformance optimization skillsSystem design and architectureProduction monitoring and troubleshootingSoft SkillsStrong problem-solving abilitiesExcellent communication skillsAttention to detailTeam collaborationTechnical documentation skillsProject management capabilities