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Lead technical accounting initiatives and drive excellence in financial reporting and controls environment for Faire, an online wholesale marketplace. Responsibilities include IPO readiness, researching technical accounting positions, collaborating on accounting implications, leading adoption of new accounting pronouncements, assisting with audits, documenting financial processes, and more.

As a Senior Staff Back-end Engineer at Faire, you will develop next generation search applications, optimize search infrastructure, and collaborate with cross-functional teams to employ machine learning for enhancing search performance and relevance in the marketplace.

The Staff Analytics Engineer will lead technical projects related to core data infrastructure, optimize data processing systems, ensure data quality, and collaborate with technology leads and stakeholders to drive data initiatives.

The Staff Data Scientist / Machine Learning Engineer will work on optimizing search algorithms, personalizing recommendations, and building advertising solutions for Faire's platform using machine learning techniques. Responsibilities include collaborating with teams to develop solutions that drive business impact and support local retailers.

The CRM Lifecycle Marketing Manager will ideate, execute, and optimize email campaigns to drive customer engagement and conversion. This role involves collaboration with Product, Data, and Design teams to align marketing strategies with business objectives, analyze campaign performance, and implement data-driven insights to enhance lifecycle marketing efforts.

The Staff Software Engineer - Data Platforms will lead the Core Data Infrastructure team, developing a strategic vision, optimizing processes, and enhancing data infrastructure capabilities. They will ensure security and data quality standards are met while collaborating with cross-functional teams on data-driven initiatives.

The role involves designing and building scalable machine learning systems for Faire's wholesale marketplace. Responsibilities include creating Machine-Learning-as-a-service components, a model training framework, and deep learning infrastructure while providing mentorship to ML engineers.