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Machine Learning Engineer at Bree | JobVerse
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Machine Learning Engineer
Bree
Website
LinkedIn
Machine Learning Engineer
Canada
Full Time
2 hours ago
$130,000 - $230,000 CAD
No Sponsorship
Apply Now
Key skills
AWS
Azure
Cloud
Docker
Google Cloud Platform
Kubernetes
NoSQL
Numpy
Pandas
Python
PyTorch
Scikit-Learn
SQL
Machine Learning
ML
scikit-learn
NumPy
MLOps
LightGBM
MLflow
Kubeflow
GCP
Google Cloud
SageMaker
CI/CD
About this role
Role Overview
Design, develop, and deploy end-to-end machine learning pipelines, ensuring efficiency in training, validation, and inference.
Implement MLOps best practices, including CI/CD for ML models, model versioning, monitoring, and retraining strategies.
Optimize ML models using feature engineering, hyperparameter tuning, and scalable inference techniques.
Work with structured and unstructured data, leveraging Pandas, NumPy, and SQL for efficient data manipulation.
Apply machine learning design patterns to build modular, reusable, and production-ready models.
Collaborate with data engineers to develop high-performance data pipelines for training and inference.
Deploy and manage models on cloud platforms (AWS, GCP, Azure) with containerization and orchestration tools like Docker and Kubernetes.
Maintain model performance by implementing continuous monitoring, bias detection, and explainability techniques.
Requirements
Proficiency in Python and familiarity with ML libraries like Scikit-learn, LightGBM, and PyTorch.
Strong understanding of machine learning algorithms, including supervised and unsupervised learning techniques.
Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker for tracking experiments and automating workflows.
Hands-on experience with data manipulation libraries (Pandas, NumPy) and databases (SQL, NoSQL).
Knowledge of cloud-based ML deployment and infrastructure management.
Ability to implement real-time and batch inference pipelines efficiently.
Strong analytical and problem-solving skills to translate business needs into scalable ML solutions.
Eagerness to work in a fast-paced environment and continuously refine ML processes for efficiency and accuracy.
Tech Stack
AWS
Azure
Cloud
Docker
Google Cloud Platform
Kubernetes
NoSQL
Numpy
Pandas
Python
PyTorch
Scikit-Learn
SQL
Benefits
Top of the market compensation for top performers
Comprehensive dental / vision
$1,500 annual learning stipend
$1,000 annual wellness stipend
$250 monthly lunch stipend
2 annual company retreats
Parental leave
Unlimited PTO
Apply Now
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