Lead Machine Learning and AI-based Information Processing Specialist

Your tasks

Development of algorithms in the field of machine learning and information processing methods for fraud monitoring and revenue assurance. Software development. Support of current software versions. Participation (and leadership) in software testing and maintenance.

Requirements

Higher education (Bachelor's + Master's) in Applied Mathematics and Computer Science, Mathematics, or related disciplines Certificates in ML/AI from Amazon, Google, Nvidia (at least one is mandatory) English language (B2+ level for analyzing international professional publications, confirmed by a certificate) Work experience (documented): 5+ years of commercial development in ML/Data Science GitHub project portfolio Publications in the field of ML/AI in peer-reviewed VAK scientific journals Participation in ML competitions. Kaggle is preferred - minimum 1-2 top 10 finishes in the private leaderboard

Responsibilities:

• Development of algorithms in the field of machine learning and information processing methods for fraud monitoring and revenue assurance
• Software development
• Support of current software versions
• Participation (and leadership) in software testing and maintenance

Requirements:

1. Mandatory technical skills:

1.1. Programming languages:

• Professional proficiency in Python
• Basic knowledge of SQL
• Knowledge of C++

1.2. ML frameworks and libraries:

• TensorFlow
• PyTorch
• Keras
• scikit-learn
• XGBoost
• Catboost

1.3. Data processing:

• Pandas
• NumPy
• Spark

1.4. ML algorithms:

• Deep learning
• NLP
• Computer vision
• Recommender systems
• Classical methods (regression, clustering, etc.)
• LLM

1.5. Infrastructure:

• Knowledge of Docker, Kubernetes, Airflow, Kafka
• Understanding of MLOps practices (monitoring, model versioning).

1.6. Working with data:

• Ability to work with big data
• Experience in preprocessing, cleaning, and feature engineering
• Knowledge of databases: relational (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra)

1.7. Software development and deployment:

• Experience in creating, training, and deploying LLM in production
• Knowledge of CI/CD tools (Jenkins, GitLab CI)
• Ability to optimize models for speed and scalability

1.8. Mathematical background:

• Understanding of linear algebra, statistics, and optimization methods

Desired skills:

• Knowledge of neural network architectures (Transformer, CNN, RNN)
• Experience with AutoML tools (MLflow, Kubeflow)
• Domain knowledge in company-specific areas (communication systems)
• Participation in open-source projects.

Higher education — specialist degree, master's degree; Experience: 5 years

Other

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