Cloud ML - AI Tech Lead (NLP)

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Position Summary:

We are seeking a Cloud ML/AI technical leader to join our team. Your role will be to lead a team of specialists on Cloud and Natural Language Processing (NLP) in technical decision-making, planning and innovation. The project involves maintaining a largescale system on a global scale while innovating on new features that may be useful to our stakeholders. Familiarity with AI/ML Concepts, cloud services and web backend technologies is required. Knowledge in NLP systems, data engineering and academic research skills is also welcome. The team also delves into more advanced topics in ML/AI such as LLMs, Transformers and Low Resource NLP as part of innovation tasks.

As tech lead, your role is to act as intermediary between the project lead and individual contributors to ensure that tasks are completed correctly and in a timely manner. You are also expected to provide subject matter expertise in technical decision-making and research direction. Other tasks, include requirement analysis, task delegation, and occasional stakeholder management.

Job Responsibilities

·        Requirement Analysis, Identification of timelines and deliverables

·        Technical Documentation and Reporting

·        Occasional Stakeholder Management and Day-to-day communications

·        Technical decision-making along with the team specialists

·        Developer contribution and issue resolution

·        Research new approach, solutions, and architecture that can contribute to the project’s improvement and evolution

Job Requirements

·        Experience in working in or leading a cloud, data engineering using python-based tools

·        Python and Popular Libraries (Pandas, Numpy, Multiprocessing etc.)

·        REST API, Python Web Backend or related technologies

·        Database Tools (MongoDB, MySql, etc.)

·        Machine Learning Concepts (Neural Networks, Transformers, Convolutional Models, Parameter Optimization)

·        ETL design, implementation and maintenance

Preferred Experience:

·        Natural Language Processing (NLP) Systems

·        Hands-on experience working in data warehousing, data architecture and/or data engineering environments at an enterprise scale.

·        Academic research and publication skills