ML Practice Leader

A Practice Leader is the first point of contact for their direct reports, and they liaise and relay information between senior leaders, HR, and engineers.

The role of a Practice Leader is probably the most important because this is the first line of people management, and it provides things to be done. On the one hand, a PL is a part of the Practice, so this person must be at least senior-level in their specialty. On the other hand, a Practice Leader is a people manager.

The complete list of requirements looks like the following:
— Practical experience and strong understanding of Python patterns & best practices.
— Strong understanding of ML project lifecycle.
— Practical experience with creating training datasets involving human annotators.
— Experience with writing Deep Learning models from scratch.
— Experience in >1 of the following areas: NLP, CV, forecasting, recommender systems.
— Strong experience with agentic workflows, RAG architecture, and GraphRAG.
— Experience and in-depth understanding of transformers.
— Practical experience with /AWS/other cloud/open source alternatives/ MLOps platforms, frameworks, and libraries.
— Practical experience with model post-production & maintenance: model and data monitoring, retraining automation, etc.
— Ability to make reusable components of ML pipelines.
— Practical experience with a variety of data sources (OLTP, OLAP, DataLake, Streaming).
— Experience in DataOps or ML/MLOps would be a significant plus.
— Ability to explain decisions, status, and roadmap to non-technical customer representatives.
— Experience in team/department leadership.
— Ability to teach and mentor. The role assumes providing employees with their career path and helping them achieve goals.
— Diplomatic skills. It means more than just “communication skills” and includes ethics, empathy, compassion, and the ability to resolve conflicts.
— Calmness. People are complicated, and you need to be ready for any objectives or misunderstandings.

Responsibilities:
— Build effective teams.
— Participate in meetups, conferences, and build community.
— Share best practices and culture with the team.
— Mentor engineers, coach Team Leads, and encourage others to share knowledge.
— Have technical excellence and be an influencer in different teams/projects.
— Hire and onboard newcomers.
— Conduct performance reviews, 1-on-1 meetings.
— Identify and address team gaps in knowledge.
— Evaluate, improve, and maintain processes.
— Сollaborate with other managers across the company.
— Communicate and follow the company’s mission, vision, and values.