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Senior Machine Learning Engineer Jobs in Quebec (NOW HIRING)

Jumio

Senior Machine Learning Engineer

Montreal, QC

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 ...

LawZero

Senior ML Research Developer

Montreal, QC

We are seeking a senior machine learning (ML) research developer to join our team working on a novel AI safety agenda. In this role, you will work closely with ML research scientists to solve ...

LawZero

Machine Learning Manager

Montreal, QC

We are seeking a Machine Learning (ML) Manager to join our growing team dedicated to a novel AI ... You will bridge the gap between cutting-edge scientific theory and large-scale engineering ...

Targeted Talent

Senior Deep Learning Engineer

Montreal, QC · On-site +1

$130K - $180K/yr

We're hiring 3 Senior Deep Learning Engineers to join our Neural Networks team. Your primary focus will be optimizing neural networks to efficiently run on our hardware and building a model ...

Targeted Talent

Senior Deep Learning Engineer

Quebec, QC · On-site +1

$130K - $180K/yr

We're hiring 3 Senior Deep Learning Engineers to join our Neural Networks team. Your primary focus will be optimizing neural networks to efficiently run on our hardware and building a model ...

Targeted Talent

Senior Deep Learning Engineer

Quebec, QC · On-site +1

$130K - $180K/yr

We're hiring 3 Senior Deep Learning Engineers to join our Neural Networks team. Your primary focus will be optimizing neural networks to efficiently run on our hardware and building a model ...

Targeted Talent

Senior Deep Learning Engineer

Montreal, QC · On-site +1

$130K - $180K/yr

We're hiring 3 Senior Deep Learning Engineers to join our Neural Networks team. Your primary focus will be optimizing neural networks to efficiently run on our hardware and building a model ...

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Senior Machine Learning Engineer information

What are some common challenges Senior Machine Learning Engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What does a Senior Machine Learning Engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are the key skills and qualifications needed to thrive as a Senior Machine Learning Engineer, and why are they important?

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

What is the difference between Senior Machine Learning Engineer vs Data Scientist?

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Quebec? The most popular types of Machine Learning Engineer jobs in Quebec are:
What are popular job titles related to Senior Machine Learning Engineer jobs in Quebec? For Senior Machine Learning Engineer jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Senior Machine Learning Engineer jobs in Quebec look for? The top searched job categories for Senior Machine Learning Engineer jobs in Quebec are:
What cities in Quebec are hiring for Senior Machine Learning Engineer jobs? Cities in Quebec with the most Senior Machine Learning Engineer job openings:
Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in Quebec as of July 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 85% Physical, 5% Hybrid, and 10% Remote job distribution.
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Jumio

Montreal, QC

Other

Posted 25 days ago

Job description

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

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