Senior ML Engineer

The Senior ML Engineer will spearhead the end-to-end development, deployment, and

stewardship of machine-learning solutions that power credit-risk, collections-strategy,

conversion-optimisation, and fraud-detection processes in MD Finance. Working hand-

in-hand with Risk, Product, Operational and other teams, the role will translate business

goals into robust models, ensure their ongoing performance, and identify new AI/ML

opportunities that raise the company’s bottom line.

Professional qualifications

• 7+ years’ experience in Machine Learning / Data Science, with 3+ years in credit-


• lending organisations.


• Demonstrated delivery and productionisation of Probability-of-Default (PD)models, credit-limit strategies, fraud-detection, conversion-uplift, and collections-


• optimisation models.


• Advanced Python proficiency and solid grasp of modern ML algorithms, feature


• engineering, and model-evaluation best practices.


• Ability to write, structure, and optimise complex SQL queries.


• Deep understanding of the credit lifecycle, especially online lending workflows.


• Proven skill in sourcing, cleansing, and generating features from data sets.


• Comfortable setting up and maintaining modelling environments (local, cloud, or


• on-prem).


• Detail-oriented, accountable, and committed to both team and individual targets.


• English B1 or higher.

Preferred / bonus qualifications

• Practical experience with LLM solutions:

• Using commercial APIs (e.g., OpenAI, Anthropic, etc.).


• Self-hosting of open-source models


• Fine-tuning of open-source models.


• Building voice chatbots.


• Building RAG chatbots.

• Experience with Computer Vision models for document or image processing.


• Building ML pipelines and deploying models to production.


• Creating executive dashboards and model reports in Power BI.

Main responsibilities

• Design, train, and deploy probability of default models.


• Build credit-limit strategies.


• Discover and scope AI/ML opportunities that boost efficiency and revenue of the company, including collections optimisation, fraud control, conversion lift, etc.


• Analyse data sources and engineer features for modelling.


• Produce and update internal model documentation.


• Implement model monitoring.


• Plan and execute A/B tests.


• Build Computer Vision pipelines to automate lending workflows.


• Develop LLM-based solutions that streamline internal processes or enhance customer experience.

Expected results

• Implemented probability of default models and credit-limit strategies.


• Launched A/B tests for models that potentially can boost the efficiency and/or revenue of the company.


• Thorough, audit-ready documentation for models.

What We Offer

• Join a fast-scaling FinTech company where your decisions shape the business and your contributions truly matter.


• Enjoy 20 paid days off annually, flexible scheduling, and a supportive, people-first culture.
  


• Learning, sports and medical insurance compensation.


• Work in an international, agile team with ambitious goals, modern tools, and a strong sense of purpose.