Chief Technology Officer for AI

Qualifications

• They should also have expertise in optimizing efficiency of distributed training systems and/or inference systems, experience building out high performance computing infrastructure teams at scale, and a passion for helping to build a diverse, equitable, inclusive culture
• If you are comfortable with ambiguity and rapid change, and take pride in building and operating scalable, reliable, secure systems, we encourage you to apply

Responsibilities

• As a key member of our organization, you will be responsible for designing, developing, and deploying scalable, secure, and reliable AI infrastructure that meets the evolving needs of our business
• The successful candidate will have a strong background in MLOps and Data Ops lifecycle, feature engineering, training, validation, tracking, inferencing, experimentation, monitoring, security, Lambda processing, SAGA patterns, data pipelines & warehousing, data extraction as well as data preparation for large-scale machine learning models
• Design and build development and production platforms that power our products, enabling reliability and security at scale
• Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready
• Contribute to projects that require cutting-edge technology and innovative approaches
• Manage and build a diverse team of high-performing AI and ML Infrastructure engineers
• Guide and advise product engineering teams on best practices for ensuring observable, scalable and secure systems
• Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think

Full Description

Key Responsibilities

We are seeking a highly skilled and experienced Director of AI Infrastructure to join our team. As a key member of our organization, you will be responsible for designing, developing, and deploying scalable, secure, and reliable AI infrastructure that meets the evolving needs of our business.

The successful candidate will have a strong background in MLOps and Data Ops lifecycle, feature engineering, training, validation, tracking, inferencing, experimentation, monitoring, security, Lambda processing, SAGA patterns, data pipelines & warehousing, data extraction as well as data preparation for large-scale machine learning models. They should also have expertise in optimizing efficiency of distributed training systems and/or inference systems, experience building out high performance computing infrastructure teams at scale, and a passion for helping to build a diverse, equitable, inclusive culture.

If you are comfortable with ambiguity and rapid change, and take pride in building and operating scalable, reliable, secure systems, we encourage you to apply.

• Main Responsibilities:

• Design and build development and production platforms that power our products, enabling reliability and security at scale

• Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches.

• Manage and build a diverse team of high-performing AI and ML Infrastructure engineers.

• Guide and advise product engineering teams on best practices for ensuring observable, scalable and secure systems.

• Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think.