Senior Machine Learning Engineer
1 day ago
Winnipeg MB, Winnipeg Census Division, MB; Manitoba, Canada
Placements24
Full-time
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Apply statistical modeling and deep learning expertise as a Senior Machine Learning Engineer on a fully remote, asynchronous team. Build intelligent systems from large-scale datasets.
This senior role develops, implements, and deploys advanced machine learning models. You will build pipelines, support production systems, and contribute to ML infrastructure architecture. Collaboration spans data scientists, software engineers, and product managers while MLOps practices support continuous delivery and monitoring.
Key Responsibilities
Design state-of-the-art machine learning models and algorithmsBuild pipelines for preprocessing, feature engineering, training, and evaluationDeploy production models for scalability, reliability, and performanceImplement MLOps practices for integration, delivery, and monitoringMentor junior engineers and share team knowledgeRequirements:
Six years of professional machine learning engineering experienceMaster’s or Ph.
D. in a quantitative related fieldStrong Python and TensorFlow, PyTorch, scikit-learn, or Keras proficiencyExperience with MLflow, Kubeflow, Docker, or KubernetesStrong analytical, communication, and independent project-management abilitiesUse statistical modeling, deep learning, Python, and MLOps to deliver responsible machine learning systems remotely.
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This senior role develops, implements, and deploys advanced machine learning models. You will build pipelines, support production systems, and contribute to ML infrastructure architecture. Collaboration spans data scientists, software engineers, and product managers while MLOps practices support continuous delivery and monitoring.
Key Responsibilities
Design state-of-the-art machine learning models and algorithmsBuild pipelines for preprocessing, feature engineering, training, and evaluationDeploy production models for scalability, reliability, and performanceImplement MLOps practices for integration, delivery, and monitoringMentor junior engineers and share team knowledgeRequirements:
Six years of professional machine learning engineering experienceMaster’s or Ph.
D. in a quantitative related fieldStrong Python and TensorFlow, PyTorch, scikit-learn, or Keras proficiencyExperience with MLflow, Kubeflow, Docker, or KubernetesStrong analytical, communication, and independent project-management abilitiesUse statistical modeling, deep learning, Python, and MLOps to deliver responsible machine learning systems remotely.
#J-18808-Ljbffr