Machine Learning Engineer - (Computer Vision) New Montreal

Jumio; Montreal (administrative region); Hybrid; CAD 120,000 - 190,000; Full time

Job summary

Jumio in Montreal is seeking a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to design and scale face recognition systems in production. You will build and train models, owning ML systems end-to-end on AWS.

The final level for this role will be determined after interviews. You’ll lead the design of CV biometrics systems, benchmark fairness, and own deployment in multi-GPU AWS environments, while mentoring other ML engineers and ensuring

Qualifications

• 5+ years of ML experience with biometrics or face analysis preferred.
• Experience building production ML pipelines end-to-end.

Responsibilities

• Lead design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition).
• Architect, train, and optimize models using PyTorch, TensorFlow, and/or JAX.
• Own end-to-end ML pipelines from data ingestion to deployment; design automated data ingestion/cleaning.
• Production engineering: optimize models for low-latency inference and deployment on AWS.
• Mentor ML engineers and drive best practices across the CV team.

Skills

Biometrics

Computer vision

Python

End-to-end ML

Fairness & Ethics

Tools

PyTorch

TensorFlow

JAX

Airflow

AWS/SageMaker

Job description

Montreal

We’re looking for 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. 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.

What You’ll Do

• 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 We’re Looking For

• Experience: 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 Have

• 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.

Jumio is a collaboration of people with different ideas, strengths, interests and cultures. We welcome applications and colleagues from all backgrounds and of all statuses.

About Jumio:

Jumio is a B2B technology company dedicated to eradicating online identity fraud, money laundering and other financial crimes to help make the internet safer. We leverage AI, biometrics, machine learning, liveness detection and automation to create solutions that are trusted by leading brands worldwide and respected by industry thought leaders.

Jumio is the leading provider of online identity verification, eKYC and AML solutions. With a global footprint, we’re expanding the team to meet strong client demand across a range of industries including Financial Services, Travel, Sharing Economy, Fintech, Gaming, and others.

At Jumio, we value belonging and believe in fostering an environment where a diversity of perspectives can thrive. Your responses will help us to reduce bias and increase diversity and inclusion across the company.

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Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file.

Voluntary Self-Identification

For government reporting purposes, we ask candidates to respond to the below self-identification survey.Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiringprocess or thereafter. Any information that you do provide will be recorded and maintained in aconfidential file.

As set forth in Jumio’s Equal Employment Opportunity policy,we do not discriminate on the basis of any protected group status under any applicable law.

If you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection.As a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measurethe effectiveness of the outreach and positive recruitment efforts we undertake pursuant to VEVRAA. Classification of protected categoriesis as follows:

A "disabled veteran" is one of the following: a veteran of the U.S. military, ground, naval or air service who is entitled to compensation (or who but for the receipt of military retired pay would be entitled to compensation) under laws administered by the Secretary of Veterans Affairs; or a person who was discharged or released from active duty because of a service-connected disability.

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