Jumio

Identity verification SaaS using biometrics

Senior Machine Learning Engineer

Computer VisionConfirmed live in the last 24 hours

Full-timeMontreal, QC, CanadaNo salary listedIn-person

About the Job

Requirements

Have 5 or more years of industry experience in machine learning focused on computer vision, such as image classification, object detection, segmentation, image quality, or generative models.
Have strong computer vision fundamentals.
Be aware of algorithmic bias and willing to learn domain-specific fairness practices.
Have strong proficiency in Python and related libraries such as Pillow, OpenCV, and PyTorch, and write clean, modular, production-ready code.
Have experience designing or contributing to machine-learning pipelines and familiarity with orchestration tools such as Airflow.
Have experience with GPU-based training and deploying machine-learning services on AWS.

Responsibilities

Design and develop computer vision models and pipelines for biometrics use cases such as face detection, quality assessment, and recognition.
Collaborate on benchmarking models across datasets and operating conditions.
Train and optimize models using PyTorch, TensorFlow, and/or JAX.
Contribute to end-to-end machine-learning pipelines from data ingestion to deployment, including helping design automated Airflow pipelines for data ingestion and cleaning.
Optimize models for low-latency inference using quantization, distillation, TensorRT, and/or ONNX, and support deployment on AWS.
Collaborate with and mentor machine-learning engineers, and contribute to technical best practices across the computer vision team.

Desired Qualifications

Have research publications in leading computer vision venues such as CVPR, ICCV, or ECCV.
Be familiar with vector databases and approximate nearest-neighbor search.
Have experience with generative adversarial networks or diffusion models for data augmentation.
Have mobile or edge experience with Core ML, LiteRT, and/or TensorFlow Lite.
Be familiar with privacy, security, and compliance considerations in sensitive machine-learning applications.

We're looking for a Senior Machine Learning Engineer with strong computer vision expertise to join our Biometrics team. You'll ramp up on the biometrics domain while contributing to the design, training, and scaling of our 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

Design and develop computer vision models and pipelines, contributing to biometrics use cases such as face detection, quality assessment, and recognition
Collaborate on benchmarking of models across datasets and operating conditions
Train and optimize models using PyTorch, TensorFlow, and/or JAX
Contribute to end-to-end ML pipelines, from data ingestion to deployment. Help design automated pipelines (Airflow) for data ingestion and cleaning.
Production Engineering: Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and support deployment on AWS.
Collaborate with and mentor ML engineers, and contribute to technical best practices across the Computer Vision team.

What We’re Looking For

Experience: 5+ years of industry experience in Machine Learning with a focus on Computer Vision (e.g., image classification, object detection, segmentation, image quality, generative models)
Strong Computer Vision fundamentals
Fairness & Ethics: Awareness of algorithmic bias and willingness to learn domain-specific fairness practices
Strong Engineering: Strong proficiency in Python (Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code
Systems Architecture: Experience designing or contributing to ML pipelines and familiarity with orchestration tools like Airflow
Cloud Native: Experience with GPU-based training and deploying ML services on AWS

Nice to Have

Research Publications in top computer vision venues (CVPR, ICCV, ECCV)
Large Scale Search: Familiarity with vector databases and ANN search
Synthetic Data: Experience with GANs or diffusion models for data augmentation
Mobile/Edge Experience: CoreML, LiteRT, and/or TFLite
Familiarity with privacy, security, and compliance considerations in sensitive ML applications

Jumio Values:

IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation

Equal Opportunities:

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.

Applicant Data Privacy

We will only use your personal information in connection with Jumio’s application, recruitment, and hiring processes, as described in Jumio’s Applicant Privacy Notice. If you have any questions or comments, please send an email to [email protected].

About the Company

Jumio

Identity verification SaaS using biometrics

Jumio provides identity verification and authentication services through a SaaS platform to help businesses fight fraud and stay compliant during customer onboarding and ongoing checks. The platform uses artificial intelligence, face-based biometrics, computer vision, and certified liveness detection to verify real-world identities, including document verification and risk assessments. It combines multiple verification methods within a single, scalable system and serves clients across financial services, marketplaces, and sharing platforms in 200+ countries. Its goal is to let organizations onboard new customers quickly and securely while minimizing fraud and complying with regulations.

Company size: 501-1,000
Company stage: Growth Equity (Non-Venture Capital)
Total funding: $205.4M
Headquarters: Palo Alto, CA
Founded: 2010

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