Provectus helps companies adopt ML/AI to transform the ways they operate, compete, and drive value. The focus of the company is on building ML Infrastructure to drive end-to-end AI transformations, assisting businesses in adopting the right AI use cases, and scaling their AI initiatives organization-wide in such industries as Healthcare & Life Sciences, Retail & CPG, Media & Entertainment, Manufacturing, and Internet businesses. The role of a Practice Leader is the most important for the company’s Machine Learning practice because it is not only about managing people but also requires things to be done. A Practice Leader must have sufficient technical experience to maintain and demonstrate the best market practices while keeping abreast of the latest technologies. **Requirements**: Technical: - Strong understanding of ML project lifecycle. - Experience in >1 of the following areas: NLP, CV, forecasting, recommender systems, reinforcement learning. - Experience in productionizing of ML models (different modalities). - Experience with writing deep learning models from scratch. - Ability to make reusable components of ML pipelines. - Ability to justify and explain design choices one makes. - Practical experience with model post-production & maintenance: model and data monitoring, retraining automation, etc. - Practical experience with /AWS/other cloud/open source alternatives/ MLOps platforms, frameworks, and libraries. - Strong understanding of Python patterns & best practices. - Practical experience with creating training datasets involving human annotators. - Practical experience with a variety of data sources (OLTP, OLAP, DataLake, Streaming). - Practical experience with Spark, Dask, or similar (distributed data processing). Management: - Ability to explain decisions, status, and roadmap to the development team. - Ability to explain decisions, status, and roadmap to non-technical customer representatives - Experience in team/department leadership. - Relationship/team building. Leadership requires building and maintaining a solid and collaborative team of individuals working toward the same goal. - Ability to teach and mentor. The role assumes providing employees with their career path and helping them achieve their 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 it is required to be ready for any objectives or misunderstandings. **Responsibilities**: - Build effective teams of ML engineers. - Contribute to best practices of the team. - Share best practices and culture with the team. - Mentor engineers, coach Team Leads, and encourage others to share knowledge. - Participate in meetups, and conferences, and build community. - Have technical excellence and be an influencer in different teams/projects. - Hire and onboard newcomers. - Conduct performance reviews and 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.