Machine Learning Practice Leader/ AI Engineering Manager

at  Provectus

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.

• 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.