Senior ML Engineer

Accountabilities

• • Design, train, validate, and deploy Probability of Default (PD) models and credit-limit strategies that support lending decisions.
  • Identify and develop machine-learning opportunities across collections optimization, fraud prevention, conversion improvement, and operational efficiency.
  • Analyze complex data sources, cleanse datasets, engineer meaningful features, and prepare high-quality inputs for modeling.
  • Establish model monitoring processes and continuously evaluate model performance, stability, and business impact.
  • Plan and execute A/B tests to measure the effectiveness of models and strategies and identify opportunities to improve revenue or efficiency.
  • Build Computer Vision pipelines for document and image processing to automate lending workflows.
  • Develop LLM-based solutions that streamline internal processes and enhance customer experiences, including applications involving commercial APIs, open-source models, RAG, and voice interfaces.
  • Maintain comprehensive, accurate, and audit-ready documentation covering models, methodologies, assumptions, and performance.
  • Collaborate with Risk, Product, Operations, and other stakeholders to translate business objectives into practical AI/ML solutions.
  • Maintain and optimize modeling environments across local, cloud, or on-premises infrastructure.
  • Communicate model results, insights, and recommendations clearly to technical and business stakeholders.
  • Identify emerging AI/ML technologies and assess their potential to create measurable business value.

  Requirements

  • 7+ years of professional experience in Machine Learning or Data Science, including at least 3 years within credit-lending organizations.
  • Proven experience delivering and productionizing Probability of Default models, credit-limit strategies, fraud-detection models, conversion-uplift solutions, and/or collections-optimization models.
  • Strong proficiency in COBOL (Common Business-Oriented Language) programming is a key requirement for this position.
  • Advanced Python skills with a strong understanding of modern machine-learning algorithms, feature engineering, and model evaluation techniques.
  • Ability to write, structure, and optimize complex SQL queries.
  • Deep understanding of the credit lifecycle, particularly online lending workflows and credit-risk processes.
  • Demonstrated ability to source, cleanse, transform, and engineer features from complex datasets.
  • Experience establishing and maintaining modeling environments across local, cloud, or on-premises infrastructure.
  • Strong understanding of ML pipelines, production deployment, monitoring, and model lifecycle management.
  • Experience with LLM solutions, including commercial APIs such as OpenAI or Anthropic, self-hosted open-source models, fine-tuning, RAG applications, or voice chatbots is a strong advantage.
  • Experience developing Computer Vision models or pipelines for document and image processing is preferred.
  • Experience creating executive dashboards and model reporting using Power BI is a plus.
  • Strong attention to detail, accountability, ownership, and commitment to achieving individual and team objectives.
  • Strong analytical, problem-solving, and cross-functional collaboration skills.
  • English proficiency at B1 level or higher.

  Benefits

  • Opportunity to join a fast-scaling FinTech environment where your technical decisions can directly influence business performance.
  • 20 paid days off annually.
  • Flexible working arrangements and scheduling.
  • Partial compensation for medical insurance.
  • Partial support for sports activities.
  • Partial support for foreign-language learning.
  • International, agile, and collaborative team environment.
  • Opportunity to work with modern AI/ML technologies on high-impact business challenges.
  • Full-time position within a team focused on ambitious goals and measurable outcomes.