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Medium — remote mid-level ML role with biometric specialization reduces broad applicant competition.
High — specialized computer vision, biometrics and fairness experience limits cross-industry transferability.
High — mandatory 5+ years, 3+ years biometrics, and specific ML/CV production and cloud skills required.
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Lead design and development of computer vision biometric systems focused on face recognition and attributes.
Own end-to-end ML pipelines including data ingestion, model training, optimization, and deployment on AWS.
Conduct fairness analysis, optimize models for low-latency inference, and mentor ML engineers on technical best practices.
5+ years in Machine Learning with at least 3 years in Biometrics or Face Analysis.
Proficiency in Python and ML/vision libraries (PyTorch, TensorFlow, OpenCV).
Experience designing end-to-end ML pipelines and using workflow orchestrators like Airflow.
Hands-on experience deploying and scaling ML services on AWS including SageMaker and multi-GPU clusters.
Deep expertise in computer vision, face recognition, and biometric fairness techniques.
Proven ability to build scalable production ML systems with focus on bias mitigation and performance optimization.
Experience mentoring engineers and driving technical standards in a Computer Vision or Biometrics focused team.