Manager, RDU IT – Data Science

Description

• Lead the development and refinement of Generative AI systems and applications using state-of-the-art models to solve complex business problems.
• Contribute to the development and maintenance of MLOps infrastructure and tools for Machine Learning and Generative AI models.
• Participate in the full lifecycle development of Generative AI agents, ensuring meaningful interaction with users or environments.
• Support the integration of pre-trained Generative AI models into custom applications for new functionalities.
• Collaborate with senior engineers to design interactive systems using Generative AI for dynamic content or decision support.
• Contribute to building and maintaining infrastructure for running Generative AI applications.
• Aid in implementing user interfaces or API endpoints for seamless interaction with Generative AI functionalities.
• Assist with data pipelines and preprocessing steps for feeding Generative AI models with appropriate data.
• Help monitor the operational health of Generative AI applications in production, identifying areas for improvement or optimization.
• Contribute to developing assets, frameworks, and reusable components for Generative AI, Machine Learning, and MLOps practices.
• Engage with stakeholders to gather feedback and iteratively improve upon Generative AI applications' features and capabilities.
• Support the integration of Generative AI models within the Machine Learning ecosystem, ensuring ethical use and business relevance.
• Assist with monitoring and governance of Generative AI models to align with evolving business and regulatory requirements.

Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field
• 3+ years of experience in Machine Learning, data science, or software development
• Familiarity with ML Engineering concepts and tools, including Docker/containerization, and basic model upkeep
• Exposure to CICD practices and familiarity with tools such as GitHub Actions, Jenkins, or Bitbucket pipelines
• Experience with Python and familiarity with ML libraries such as Tensorflow, Keras, or PyTorch
• Experience with cloud computing platforms, such as AWS, Azure or GCP
• Understanding of software engineering principles and exposure to agile methodologies
• Good communication and collaboration skills, with enthusiasm for working in a cross-functional team environment
• Proactive and eager to learn with strong analytical and problem-solving skills