Senior Machine Learning Engineer

Shape the future of banking by building production ML models that directly impact how customers experience DSK Bank. Your models will power Next Best Offer recommendations, optimize pricing strategies, detect fraud and AML risks, and enable personalized financial services for thousands of customers. Working in a startup-like environment within a leading bank, you'll take ownership of the entire ML lifecycle—from problem framing to production deployment and monitoring—knowing your work ships to real users and drives measurable business outcomes. You'll contribute to building the ML platform itself, making it easier for the entire team to deliver world-class AI solutions.

General duties:

Develop, deploy, and maintain production-grade ML models for business-critical use cases including Next Best Offer/Action, pricing optimization, anti-fraud detection, and AML (Anti-Money Laundering) models.

Own the end-to-end ML lifecycle: problem framing, data exploration, feature engineering, model training and validation, deployment, monitoring, and continuous improvement.

Design and implement robust model monitoring and retraining pipelines to ensure model performance over time.

Collaborate with Data Engineers and Software Engineers to integrate ML models into production systems and streaming/batch pipelines.

Contribute to the design and improvement of the in-house ML platform to enhance productivity and model deployment efficiency.

Work with stakeholders across the bank to understand business requirements and translate them into ML solutions.

Ensure models meet governance, compliance, and audit requirements; maintain documentation and model cards.

Requirements

Must have

3+ years of hands-on experience in ML engineering or data science roles.

Strong foundation in mathematics, statistics, ML algorithms, metrics, and loss functions.

Advanced expertise in Python and ML ecosystem (NumPy, pandas, scikit-learn).

Strong SQL skills for data manipulation and analysis.

Verbal and written English at Upper Intermediate level (B2+) or above.

Nice to have

Proven track record of deploying models to production.

Experience with gradient boosting libraries (XGBoost, CatBoost, LightGBM).

Spark skills, including complex joins, subqueries, CTEs, window functions, and large-scale data processing.

Experience with ML lifecycle tools such as MLflow, Azure Databricks, or similar platforms.

Proficiency in writing clean, efficient, scalable, and maintainable Python code.

Experience with model deployment, monitoring, and MLOps best practices.

Understanding of model validation, A/B testing, and evaluation metrics.

Experience with LLM-based applications or agentic AI frameworks (LangChain, LangGraph).

Familiarity with deep learning frameworks (PyTorch, TensorFlow, Keras).

Experience with workflow orchestration tools (Airflow, Prefect).

Knowledge of real-time model serving and streaming ML pipelines.

Experience in banking, fintech, or highly regulated industries.

Familiarity with Azure cloud services and Kubernetes.

What we offer to you:

Excellent opportunities for professional and career development in one of Bulgaria’s leading banks;

Food vouchers in the amount of 102.26 EUR per month;

25 paid holiday leave;

Additional Health Insurance;

Favorable conditions for housing and mortgage lending, as well as for bank products and services;

Annual bonus scheme depending on the achieved results;

Preferential conditions for Multisport / CoolFit card;

Great location;

Discounts in various companies;

Professional trainings for specific knowledge and skills (internal academies);

Refer a Friend Bonus.

If you are challenged by this opportunity, we would be glad to review your application.