Machine Learning Engineer Manager (AI Platform)

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

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Seniority

Senior From the posting source

Schedule

Shift type

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Weekend work

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Company

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Application

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Assessment

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Deadline

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About this role

Machine Learning Engineer Manager (AI Platform) Brazil, Sao Paulo About Us Nu is one of the largest digital financial platforms in the world, with more than 127 million customers across Brazil, Mexico, and Colombia. Guided by our mission to fight complexity and empower people, we are redefining financial services in Latin America and this is still just the beginning of the purple future we're building. About the Role AI Platform Team - The mission of the AI Platform team is bold: to democratize AI by empowering every Nubanker-not just Data Scientists-with safe, scalable, and accurate Machine Learning capabilities. We are looking for a Manager who is passionate about creating solutions that push the boundaries of our current stack. You will help us move beyond basic DS work to abstract the complexities of the entire ML lifecycle-from training and deployment to serving and governance. Why is this role open? We are scaling. Currently, our structure has grown significantly, and to ensure the organization's health and the growth of our engineers, we are opening this position to lead a dedicated squad. You will take ownership of a team that manages the base infrastructure for the entire Data Science function at Nubank. You'll be responsible for: As the ML Manager for the AI Platform , you will combine technical leadership with people management. You will lead a squad of 11 Machine Learning Engineers (varying from Senior to Intern levels) and work closely with a Staff ML Engineer and a Product Manager. - People

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