Senior Machine Learning Engineer

Jumio•Montreal, QC

45d

About The Position

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. 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.

Requirements

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
Awareness of algorithmic bias and willingness to learn domain-specific fairness practices
Strong proficiency in Python (Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code
Experience designing or contributing to ML pipelines and familiarity with orchestration tools like Airflow
Experience with GPU-based training and deploying ML services on AWS

Nice To Haves

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

Responsibilities

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.