ML Team Lead

A software development company is looking for a talented, long-term ML Team Lead. 

The company is a team of experts providing analytical services to healthcare clients. You will join an international team of first class professionals who are passionate to create products that improve quality of medical services. 

Responsibilities:

• Team Leadership and Development: Lead a small team of 2-4 data scientists focused on solving challenging problems using tabular data with large, feature-rich datasets. Create a collaborative and productive environment, support team members’ technical and professional growth;
• Software Design: Develop, maintain, and improve a complex source code base, ensuring modularity, scalability, and maintainability. Architect class structures and overall project organization to optimize for long-term development and ease of collaboration;
• Technical Task Planning and Prioritization: Work with the Product Manager to understand business goals, set task priorities, and manage team resources effectively. Recommend task prioritization strategies to increase product impact and efficiency;
• Technical Oversight and Quality Assurance: Lead the team through all stages of model development, from design to deployment, ensuring best practices in code quality, documentation, and reproducibility. Set clear, repeatable documentation standards to support scalability and knowledge sharing. Implement systems to monitor model performance and keep ML services stable;
• Cross-Functional Collaboration: Work closely with other teams (e.g., Machine Learning Engineers, MLOps, UI) to ensure ML models integrate smoothly with the overall system and align with other technical projects.

Requirements:

• 5+ years in machine learning with hands-on model development experience;
• 2+ years in a technical leadership role;
• Practical experience with Git, Airflow and MLflow (or similar tools);
• Strong Python skills with experience using popular ML libraries and tools (sklearn, CatBoost, optuna, etc);
• Build and tune models, with a focus on boosting algorithms (e.g., XGBoost, LightGBM, CatBoost), to deliver actionable insights and predictions;
• Experience with cloud platforms (AWS, GCP, Azure), especially their ML and data engineering services;
• Advanced SQL skills and experience building/managing data pipelines with Airflow or similar tools;
• Understanding of MLOps practices, including CI/CD for ML;
• English level B2 or higher.

Preferred Qualifications (Optional):

• Experience in healthcare or medical insurance projects;
• Experience with Google Cloud Platform (GCP).

Benefits: 

• Flexible working hours; 

• Remote work; 

• Interesting projects to work on; 

• Paid vacations.