Senior ML Engineer – AI Safety

Requisitos

• Experience in machine learning, data science, or software engineering, focused on AI safety, alignment, Responsible AI, or model governance
• Strong Python skills and proficiency with ML frameworks such as TensorFlow, PyTorch, or scikit-learn
• Hands-on MLOps experience including MLflow, Kubeflow, CI/CD for ML, model monitoring, versioning, and reproducible deployment
• Demonstrated knowledge of AI safety techniques: red-teaming, adversarial testing, fairness metrics, interpretability, alignment approaches
• Strong understanding of AI governance, model risk management, and regulatory expectations in financial services

Desejáveis

• Practical experience preparing documentation for audit or regulatory review
• Experience designing or running automated benchmark suites for LLMs or other GenAI systems
• Familiarity with bias detection, harm classification, content safety tooling, or policy evaluation frameworks
• Experience with regulated financial services use cases such as fraud detection, credit risk, customer service automation, or model risk m..
• Experience influencing engineering standards or mentoring engineers in AI safety, Responsible AI, or production ML practices