Machine Learning Practice Leader - AI Engineering Manager

4 days ago

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Provectus

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Mobile applications • DevOps • Enterprise Software • R&D • eCommerce

501 - 1000

Description

• 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. • 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). • 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.