Lead Computer Vision ML Engineer — Biometrics & Production

Jumio; Palo Alto (CA); Híbrido; USD 180.000 - 260.000; Jornada completa

Descripción de la vacante

Jumio in Palo Alto is seeking a Principal ML Engineer to lead the design and deployment of state-of-the-art computer vision biometrics systems, focusing on face attributes, detection, quality, and recognition.

You will architect end-to-end ML pipelines, curate balanced training data, generate synthetic samples to address quality and diversity gaps, and drive rigorous fairness analysis across diverse datasets.

Formación

• 5+ years of industry experience in Machine Learning.
• Deep expertise in computer vision and biometrics.
• Understanding sources of algorithmic bias in Computer Vision and mitigating disparate impact.
• Proficiency in Python and ML libraries; ability to write clean, production-ready code.
• Experience deploying ML models on AWS and scaling training jobs on multi-GPU clusters.

Responsabilidades

• Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition).
• Perform rigorous fairness analysis and benchmarking across datasets and operating conditions.
• Architect, train, and optimise 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.
• Curate balanced training sets and generate synthetic data to address quality and diversity gaps.
• Production Engineering: optimise models for low-latency inference and deploy on AWS.
• Mentor ML engineers, conduct code/design reviews, and drive best practices.

Conocimientos

Python

Computer Vision

Biometrics

Machine Learning

Fairness & Ethics

Mentoring

End-to-end ML pipelines

Production-ready code

Herramientas

PyTorch

TensorFlow

JAX

OpenCV

Pillow

Airflow

TensorRT/ONNX

AWS SageMaker

EC2

EKS

Descripción del empleo

Jumio in Palo Alto is seeking a Principal ML Engineer to lead the design and deployment of state-of-the-art computer vision biometrics systems, focusing on face attributes, detection, quality, and recognition.

You will architect end-to-end ML pipelines, curate balanced training data, generate synthetic samples to address quality and diversity gaps, and drive rigorous fairness analysis across diverse datasets.