Baku,
Azerbaijan
05.03.25
-
05.04.25
Working conditions
- Conduct research to evaluate the latest machine learning techniques and tools, applying them to solve business problems effectively;
- Build and support machine learning models, tools, and applications;
- Enhance existing solutions to improve performance and scalability;
- Implement feature engineering and transformation;
- Collaborate with data engineering / DevOps teams to design and maintain robust ML pipelines;
- Optimize workflows for parallel processing using GPUs and CPUs;
- Use scalable and efficient software engineering practices to integrate machine learning components into larger software ecosystems;
- Develop monitoring tools to ensure the reliability and performance of deployed ML models;
- Implement continuous integration and delivery pipelines for ML models to streamline deployment and updates;
- Utilize tools like Kubernetes or Docker for model deployment;
- Work with business stakeholders to define requirements and create design documents for features and services;
- Collaborate with cross-functional teams, including data engineers, business analysts, clients, and vendors;
- Write clean, maintainable, and efficient code aligned with best practices;
- Participate in peer code reviews and ensure high-quality deliverables;
- Manage data science projects, timelines, and deliverables;
- Provide access management support (user access, platform, application, API’s);
- Encourage continuous learning, knowledge sharing and skill development among team members;
- Ensure data privacy and adhere to ethical data handling practices;
- Meal allowance;
- Annual performance bonuses;
- Corporate health program: VIP voluntary insurance and special discounts for gyms;
- Access to Digital Learning Platforms;
- 5/2, 09.00-18.00.
Requirements
- BSc/BA in Computer Science, Computer Engineering, Math or relevant field; graduate degree in Data Science or another quantitative field or equivalent experience;
- Proven experience as a Machine Learning Engineer / Software Engineer (minimum 2 year);
- Fluent Azeri and English, Russian is a plus;
- Mastery of machine learning algorithms and techniques;
- Experience in neural networks and deep neural architectures;
- Experience with big data frameworks like Hadoop and Spark;
- Distributed computing and parallel processing for large-scale data analysis;
- Proficiency in SQL for querying and manipulating relational databases;
- Knowledge of NoSQL databases (e.g., MongoDB, Cassandra);
- Expertise in programming languages such as Python and / or C/C++, C#, Go;
- Ability to develop production-ready code and scripts;
- Proficiency in using version control systems like Git for code management and collaboration;
- Experience in model experiments tracking tools (e.g., MLflow);
- Knowledge of containerization (e.g., Docker) and orchestration tools (e.g., Kubernetes);
- Experience in deploying models in production environments;
- Knowledge of CI/CD pipelines and automated testing for data science projects;
- Effective communication skills to explain complex technical concepts to non-technical stakeholders;
- Storytelling with data to communicate findings effectively;
- Teamwork, problem-solving attitude, business understanding, critical thinking, investigation skills, innovativethinking.
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