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:
We are looking for candidates that combine good software engineering experience for ML applications, and proven people management skills.
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.
