Machine Learning Engineer (Collections)

Our Collections department is expanding its use of machine learning to optimize debt recovery, customer engagement, and operational efficiency. We're looking for a hands-on specialist to design, implement, and maintain production-ready ML models, while building the practices and infrastructure needed for sustainable, scalable use. This role is ideal for someone who thrives on applied, production-focused work and wants to shape how ML drives real impact in Collections from day one.

Challenges that await you

• Develop and deploy production-ready ML models for segmentation, outreach optimization, and risk prediction.
• Build and maintain data pipelines for model training, retraining, and monitoring.
• Collaborate with engineers to integrate models into automated workflows and decision systems.
• Define and implement best practices for ML in production (versioning, testing, monitoring).
• Translate business problems into data-driven solutions and communicate results clearly to stakeholders.

What makes you a great fit

• 2+ years of hands-on experience in applied ML with a strong focus on classic algorithms (e.g., gradient boosting, decision trees, logistic regression).
• Proficiency in Python and ML libraries such as scikit-learn, XGBoost, LightGBM.
• Strong engineering background: clean, maintainable code, Git, CI/CD, automated testing.
• Proven track record of deploying ML solutions to production.
• Solid foundation in statistics and probability theory.
• Degree from one of: MSU, MIPT, HSE, MSTU, MEPhI, NES (or similar-level institutions).
• Participation in math, physics, economics, or CS olympiads is a plus.

Your bonus skills:

• Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
• Familiarity with large language models (LLMs) and modern NLP techniques.
• Knowledge of modern ML approaches such as embeddings, transformers, or reinforcement learning.
• Exposure to cloud ML environments (AWS Sagemaker, GCP Vertex AI, Azure ML).

What We Value

• Pragmatic approach — delivering working solutions that create measurable impact.
• Ability to work in a growing ML environment with evolving processes.
• Initiative in establishing ML workflows and tools that will scale with the business.

Our ways of working

• Innovative Spirit: a commitment to creativity and groundbreaking solutions.
• Honest Feedback: valuing open, transparent communication.
• Supportive Team: a strong, collaborative community.
• Celebrating Achievements: recognizing our wins together.
• High-Tech Environment: a team full of smart and revolutionary people who dare to challenge the status quo of incumbent finances.

Our benefits

• Relocation support to Mexico with assistance for the employee and their family.
• Flexible work: hybrid or full-time from our office in Mexico.
• Healthcare Coverage.
• Education Budget: Language lessons, professional training, and certifications.
• Wellness Budget: Mental health and fitness activity reimbursements.
• Vacation policy: 20 days of annual leave and paid sick leave.