Machine Learning Engineer

We are seeking an experienced Machine Learning Engineer to design, develop, deploy, and maintain production-grade machine learning solutions.

You will be responsible for the complete machine learning lifecycle, from data preparation and experimentation to production deployment, monitoring, and continuous improvement. The role requires close collaboration with software engineers, product managers, data specialists, and international stakeholders., * Design, develop, train, validate, and optimize machine learning models.

• Build scalable and reliable machine learning pipelines.
• Prepare, clean, transform, and analyze structured and unstructured datasets.
• Perform feature engineering, model selection, hyperparameter tuning, and error analysis.
• Define appropriate model evaluation metrics and validation strategies.
• Deploy machine learning models and AI services into production environments.
• Develop and maintain APIs and backend services for model inference.
• Monitor model performance, latency, data quality, and model drift.
• Improve the reliability, scalability, and cost efficiency of machine learning systems.
• Establish reproducible experimentation, model versioning, and documentation practices.
• Collaborate with engineering and product teams to translate business requirements into technical solutions.
• Conduct code reviews and contribute to engineering standards and best practices.
• Research and evaluate new machine learning methods, frameworks, and technologies.
• Clearly communicate technical findings and recommendations to both technical and non-technical stakeholders.

Professional working proficiency in both English and Russian is mandatory due to regular communication with English- and Russian-speaking team members and stakeholders., * At least 3 years of commercial experience as a Machine Learning Engineer, AI Engineer, Data Scientist, or in a comparable technical role.

• Strong proficiency in Python.
• Production experience with one or more machine learning frameworks, including PyTorch, TensorFlow, Scikit-learn, XGBoost, or LightGBM.
• Strong understanding of supervised and unsupervised learning.
• Practical knowledge of classification, regression, clustering, ranking, forecasting, or recommendation systems.
• Experience with data preprocessing, feature engineering, model evaluation, and hyperparameter optimization.
• Strong knowledge of SQL and experience working with relational or analytical databases.
• Experience deploying machine learning models into production.
• Experience designing or integrating REST APIs.
• Working knowledge of Git, automated testing, code review, and software development best practices.
• Understanding of statistics, probability, linear algebra, and machine learning fundamentals.
• Ability to write maintainable, tested, and well-documented production code.
• Strong analytical, communication, and problem-solving skills.
• Ability to work independently and effectively within a distributed, cross-functional team.
• Professional working proficiency in English, both written and spoken.
• Professional working proficiency in Russian, both written and spoken.

Preferred Qualifications

• Experience with AWS, Microsoft Azure, or Google Cloud Platform.
• Experience with Docker and containerized model deployment.
• Knowledge of Kubernetes and cloud-native infrastructure.
• Experience with MLOps tools such as MLflow, Kubeflow, Airflow, Weights & Biases, or similar platforms.
• Experience building CI/CD pipelines for machine learning systems.
• Knowledge of model monitoring, observability, data validation, and drift detection.
• Experience with distributed data-processing technologies such as Spark.
• Experience with natural language processing, large language models, computer vision, recommendation systems, or predictive analytics.
• Familiarity with retrieval-augmented generation, vector databases, embeddings, or LLM evaluation.
• Understanding of data privacy, information security, responsible AI, and model governance.
• Experience working in an international or multilingual environment., We evaluate candidates based on professional qualifications, relevant experience, technical ability, and alignment with the requirements of the role. We are committed to maintaining a professional and inclusive recruitment process.

• AED 444,000 annualized gross base salary.
• AED 100 meal allowance for each working day, paid in addition to the base salary.
• Full-time employment.
• Four-day working week, Monday through Thursday.
• Working hours from 10:30 AM to 6:00 PM, Dubai time.
• Hybrid working arrangement.
• Modern and collaborative working environment.
• Opportunity to work on production-grade machine learning and AI systems.
• Direct involvement in technical and product decisions.
• Professional development and career-growth opportunities.