Tell me about your team: number of people, roles, processes, task distribution.

In my current ML team, there are about 8 people with the following roles:

• 2 data scientists — responsible for data research, model building, and training.
• 2 feature engineering engineers — create and maintain features, ensure data quality.
• 2 ML engineers — handle model deployment, product integration, and performance optimization.
• 1 team lead — coordinates work, assigns tasks, monitors deadlines and quality.
• 1 product manager — defines requirements and priorities.

Processes:

• Weekly meetings to discuss progress and issues.
• We use Agile with two-week sprints.
• Tasks are assigned through a tracker (Jira), with clear descriptions and readiness criteria.
• Code review and automated testing are mandatory for all changes.

This distribution helps effectively cover all stages of an ML project — from data to production.