ML Practice Leader

Practice Leader First point of contact for direct reports, and they liaise and relay information between senior leaders, HR, and engineers. 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. Requirements 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 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. #J-18808-Ljbffr