Machine Learning Engineer - IV (Biometrics)

Jumio • Montreal, QC

17d

About The Position

Jumio is seeking a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. This role involves building and training models, and owning ML systems end-to-end on AWS. The final job level will be determined after the interview process. Jumio is a B2B technology company focused on combating online identity fraud, money laundering, and other financial crimes to enhance internet safety. The company utilizes AI, biometrics, machine learning, liveness detection, and automation to deliver trusted solutions to leading global brands. As a premier provider of online identity verification, eKYC, and AML solutions, Jumio is expanding its team globally to meet strong client demand across various sectors including Financial Services, Travel, Sharing Economy, Fintech, and Gaming.

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.
• Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact.
• Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code.
• Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow.
• Cloud Native: Hands-on experience scaling training jobs on multi-GPU clusters and deploying services on AWS (SageMaker, EC2, EKS).

Nice To Haves

• Research Publications: Papers in CVPR, ICCV, ECCV, or FG related to face recognition, image quality assessment, or fairness.
• Large Scale Search: Experience with vector databases (e.g., Milvus, Faiss) and approximate nearest neighbor (ANN) search algorithms.
• Familiarity with privacy, security, and compliance in biometric systems.
• Mobile/Edge Experience: Experience porting models to edge or mobile devices utilizing frameworks such as CoreML, LiteRT, and/or TFLite.
• Synthetic Data: Experience using GANs or diffusion models to generate synthetic faces for training.
• Strong communication skills.

Responsibilities

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed
• Number of Employees: 251-500 employees