Lead Machine Learning Engineer / Applied AI Scientist
Hybrid · São Paulo, São Paulo, Brazil
Job Summary
Lead Machine Learning Engineer / Applied AI Scientist to lead high-impact research projects that bridge state-of-the-art AI and production-grade financial systems within Nubank's AI Core. You will research, design, and deploy architectures (e.g., Transformers, GNNs, Multimodal) across critical use cases like Credit, Recommendation Systems, GenAI, and real-time inference, ensuring latency, interpretability, and cost-efficiency under MLOps constraints. You will coordinate with Data, Infra, and Product stakeholders to translate research into production-ready solutions, establish technical standards for experimentation and model evaluation, and mentor senior engineers and researchers. The role includes contributing to hiring efforts and internal task forces to improve the ML lifecycle, as well as engaging in research collaborations or internal papers aligned with Nubank’s strategic goals. Hybrid work model: in São Paulo 2-3 times per week.
Required Qualifications
- 5-7+ years in applied AI/ML
- Proven track record delivering research-driven systems into production
- Deep expertise in Deep Learning architectures (Transformers, Multimodal, or GNNs)
- Strong coding skills in Python
- Proficiency with PyTorch, JAX, or TensorFlow
- Solid understanding of MLOps and deploying models at scale
- Problem-solving skills for ML formulation in messy data environments
- Excellent communication for technical and cross-functional stakeholders
- Experience with large-scale experimentation and A/B testing
- Mentorship and leadership capabilities
- Ability to participate in hiring and internal task forces
- Contributions to research collaborations or internal papers aligned with strategic goals
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