Leadership and Team Management: Direct and manage a team of cloud architects and engineers in designing and building our ML Ops platform. Foster a collaborative and innovative environment and ensure alignment with project goals.
Responsible AI Solutions: Develop solutions focused on Responsible AI, including but not limited to explainability, data drift detection, and fairness metrics. Ensure adherence to ethical AI practices.
Platform Development: Enhance the MLOps platform to improve developer experiences for data and ML engineers. This includes streamlining workflows and integrating advanced tools and technologies.
Collaboration with AI/ML Experts: Liaise with specialists in Computer Vision, NLP, Forecasting, Large Language Models (LLM), predictions, synthetic data, and other AI/ML domains. Incorporate the latest advancements from these fields into the MLOps platform.
AI/ML Reliability and Observability: Work closely with the AI/ML Reliability engineering team to develop components that ensure the reliability and observability of our platform.
Cross-Disciplinary Knowledge: While primarily focused on AI/ML, this role also requires knowledge in related disciplines such as data sciences and health/biology sciences.
Requirements & Skills:
Experience in Platform Development: Candidates should have prior experience working with platform teams, especially in the data and AI/ML space.
Cloud Platform Expertise: Proficiency in cloud platforms is essential. Experience in expanding platforms to on-premises and edge deployments is a plus.
Cross-functional Collaboration: Ability to work closely with peer cloud teams, data scientists, and product managers to align platform development with organizational objectives.
Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field is preferred, but not mandatory for candidates demonstrating significant experience and a proven track record in the field of AI/ML and platform development.; Master’s or higher degree is a plus.
Proven experience in managing and leading cloud architecture and engineering teams.
Strong background in AI/ML or Data Sciences technologies and platform development.
Demonstrated capability in leading Responsible AI initiatives.
Excellent communication, leadership, and project management skills.
