TL;DR
Lead Machine Learning Engineer (Fintech): Connecting ML models and ML-enabled systems to the infrastructure, ensuring they deliver value to customers with an accent on performance, operational, and business metrics. Focus on building and maintaining tooling and platforms to scale operations across multiple teams and deploying ML models in batch and real-time scenarios.
Location: Hybrid 2-3 times/week in Brazil, Belo Horizonte; Brazil, Campinas; Brazil, Rio de Janeiro; Brazil, Sao Paulo
Company
Nu is one of the largest digital financial platforms in the world, with more than 122 million customers across Brazil, Mexico, and Colombia.
What you will do
- Interact with stakeholders to apply data science and AI to the business.
- Monitor and maintain models and ML systems based on performance, operational, and business metrics.
- Deploy ML models in batch and real-time, including building pipelines, constructing features, and integrating models to other systems.
- Understand the ML model lifecycle, from inception to deployment and steady-state operation.
- Help build and maintain tooling and platforms to scale operations across multiple teams.
- Apply modeling and statistics concepts.
Requirements
- Programming experience with modern development techniques.
- Experience creating, deploying, and maintaining ML models and ML-enabled systems using modern frameworks.
- Familiarity with cloud-based services such as AWS, GCP, Azure, etc.
- Familiarity with software engineering and architecture principles.
- Familiarity with data engineering routines, pipelines, and job scheduling frameworks.
- Ability to navigate complex mathematical and analytical environments.
Culture & Benefits
- Chance of earning equity at hirify.global.
- Food/Meal Card.
- Public Transportation Commuting Benefit.
- NuCare – Psychological, Financial and Legal Assistance Program.
- Medical and Dental Plans.
- NuLanguage – Language Course Program.
- Learning platform of courses
- 30 days of paid vacation
- Relocation Assistance Package, if applicable.
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