Senior Machine Learning Engineer
Company shown to members 🔒 · Remote · Canada only
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First recorded by Psst: 12 October 2026. Your first 3 jobs are free to apply to (the first right away, 2 more with your email). After that, the company and the apply link are for Psst members, from $4.99 for 7 days.
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The 20-second read
- Experience
- 5+ years required
- Where you can live
- Canada only
- Skills and tools
- python, aws, machine learning, b2b, compliance, aml
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Job details
- Where you can work
- Canada
- Employment type
- Not stated by the employer
- Advertised pay
- Not stated by the employer
- Experience
- 5+ years required
- Employer publication date
- 26 June 2026
- First recorded by Psst
- 12 October 2026
- Last checked at the source
- 10 November 2026
About the job
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
The company Values
IDEAL: Integrity, Diversity, Empowerment, Accountability, Leading Innovation
Equal Opportunities
The company 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 the company
The company 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.
The company 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 the company’s application, recruitment, and hiring processes, as described in the company’s Applicant Privacy Notice. If you have any questions or comments, please send an email to [link for members] .
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