Lead ML Engineer

The company is a team of experts providing analytical services to healthcare clients is looking for a talented, long-term ML Team Lead. You will join an international team of first class professionals who are passionate to create products that improve quality of medical services.

Responsibilities:

1. Team Leadership and Development: Lead a team of 7-10 professionals, including data engineers, data scientists, MLOps engineers, and QA specialists. Create a collaborative and productive environment, support team members' technical and professional growth.
2. 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.
3. 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.
4. Architectural Solution Design and Review: Propose and evaluate technical solutions to meet project goals, and present these solutions to IT architects and the CTO. Participate actively in technical discussions to ensure solutions fit organizational standards and long-term plans.
5. Cross-Functional Collaboration: Work closely with other teams (e.g., SecOps, DevOps, UI) to ensure ML models integrate smoothly with the overall system and align with other technical projects. Interact with business and explain results of your analysis.

Requirements:

1. 5+ years in machine learning with hands-on model development experience.
2. 2+ years in a technical leadership role.
3. Practical experience with Git, Airflow and MLflow (or similar tools).
4. Strong Python skills with experience using popular ML libraries and tools (e.g., PyTorch, Hugging Face Transformers etc).
5. Experience with cloud platforms (AWS, GCP, Azure), especially their ML and data engineering services.
6. Advanced SQL skills and experience building/managing data pipelines with Airflow or similar tools.
7. Understanding of MLOps practices, including CI/CD for ML.
8. Familiarity with Kubernetes for ML service deployment and management.
9. English level B2 or higher.

Nice-to-have skills:

1. Experience in healthcare or medical insurance projects.
2. Experience with Google Cloud Platform (GCP).
3. Knowledge of Document Recognition, NLP, OpenCV, LLM.

Benefits:

1. Flexible working hours.
2. Fully remote job.
3. Opportunity to work with an international team of first-class professionals.