Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition)
Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions.
Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX
Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps.
Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS.
Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team.