Jumio
501-1000 employees
About Jumio
Jumio, the creator of Netverify® Trusted Identity as a Service, enables businesses to reduce fraud and increase customer conversions while providing a seamless customer experience. With Netverify Trusted Identity as a Service, customers have a complete identity verification solution that can be tailored to fit their specific business requirements. Netverify Trusted Identity as a Service combines biometric facial recognition, facial image matching, ID verification, and document verification to ensure the physical identity matches the real-world identity. Jumio has verified more than 50 million identities issued by over 200 countries from real-time web and mobile transactions. Jumio's solutions are used by leading companies in the financial services, sharing economy, higher education, retail, travel, and online gaming sectors. Based in Palo Alto, Jumio operates globally with offices in the US and Europe and has been the recipient of numerous awards for innovation. For more information, please visit us at www.jumio.com.
20 hours ago
Machine Learning Engineer
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Description
- We’re looking for a Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production.
- You’ll build and train models, and own ML systems end-to-end on AWS.
- The final job level for this role will be determined following the interview process.
- 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.
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Requirements
- 5+ years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis.
- Deep expertise in computer vision and biometrics, especially face recognition.
- You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact.
- Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc).
- Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow.
- Hands-on experience scaling training jobs on multi-GPU clusters and deploying services on AWS (SageMaker, EC2, EKS).
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Benefits
- Remote work options
- Diversity and inclusion initiatives
- Collaboration with a diverse team