The role involves owning and driving the end-to-end delivery of high-impact machine learning capabilities within a payments ecosystem. The individual will design and build production-grade systems that operate at scale while balancing accuracy, latency, and cost. Responsibilities include defining evaluation metrics, establishing model lifecycle standards, and ensuring robust performance governance. The position requires partnering with cross-functional teams to translate model outcomes into business impact. Additionally, the role involves leading technical execution through design reviews and mentoring to raise standards across the team.

Candidates must hold a Master’s or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Operations Research, or a related field. A minimum of 6 years of industry experience in delivering applied machine learning is required, including a proven track record of shipping models into production. Applicants must possess strong expertise in neural networks, Transformers, and model optimization techniques such as fine-tuning and distillation. Proficiency in Python, PyTorch or TensorFlow, SQL, and distributed processing systems like Spark is essential. Additionally, candidates must demonstrate experience with cloud platforms and the ability to translate complex business problems into structured technical plans.