Back
Remote mid-level ML role draws many applicants despite biometrics specialization.
Strong biometrics and computer-vision specialization limits transferability across industries.
Explicit 5+ years, mandatory biometrics experience, and specific production tooling increase filtering strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Lead design and development of biometrics computer vision systems including face detection, attributes, quality, and recognition in production.
Own end-to-end machine learning pipelines on AWS from data ingestion (including synthetic data generation) to deployment with focus on low-latency inference optimizations.
Mentor ML engineers, conduct code and design reviews, and drive technical best practices within the Computer Vision team.
5+ years industry experience in Machine Learning with at least 3 years in Biometrics or Face Analysis.
Expertise in computer vision and biometrics, specifically face recognition.
Proficiency in Python including ML and vision libraries (PyTorch, Tensorflow, OpenCV).
Experience designing end-to-end ML pipelines with workflow orchestrators (e.g., Airflow) and deploying/scaling on AWS (SageMaker, EC2, EKS).
Experienced in fairness analysis and mitigation of algorithmic bias in computer vision biometric models.
Strong systems architect with hands-on cloud native experience scaling multi-GPU training and production deployment.
Proven ability to lead and mentor engineering teams and enforce technical best practices in ML/Computer Vision contexts.