Machine Learning Engineer

Sequoia Technologies; Toronto; Hybrid; CAD 100,000 - 160,000; Full time

Job summary

Sequoia Technologies is seeking a skilled Machine Learning Engineer to develop, deploy, and optimize ML systems powering innovative AI solutions. You will collaborate with data scientists and software engineers to build scalable ML applications for clients.

The role involves designing pipelines, training models, optimizing performance, preparing large datasets, and deploying solutions into production while monitoring and iterating for improvements.

Qualifications

• Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Strong knowledge of Python and machine learning frameworks such as TensorFlow or PyTorch.
• Experience with data preprocessing, feature engineering, and model evaluation techniques.
• Understanding of cloud technologies and containerized deployments.
• Excellent problem-solving and debugging skills.

Responsibilities

• Design and develop machine learning pipelines and workflows.
• Build, train, and evaluate machine learning models.
• Optimize models for performance, scalability, and production environments.
• Prepare and process large datasets for model training and validation.
• Deploy machine learning solutions into production systems.
• Monitor model performance and implement continuous improvements.
• Collaborate with cross-functional teams on AI implementation projects.

Skills

Python

TensorFlow

PyTorch

Education

Bachelor's degree in CS/ML/AI

Master's degree in CS/ML/AI

Tools

Docker

Kubernetes

Job description

Location: Remote / Hybrid / On-site
Employment Type: Full-Time

About the Role

We are looking for a skilled Machine Learning Engineer to develop, deploy, and optimize machine learning systems that power innovative AI solutions. You will work closely with data scientists and software engineers to build scalable ML applications for our clients.

Key Responsibilities

Design and develop machine learning pipelines and workflows.

Build, train, and evaluate machine learning models.

Optimize models for performance, scalability, and production environments.

Prepare and process large datasets for model training and validation.

Deploy machine learning solutions into production systems.

Monitor model performance and implement continuous improvements.

Collaborate with cross-functional teams on AI implementation projects.

Required Qualifications

Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.

Strong knowledge of Python and machine learning frameworks such as TensorFlow or PyTorch.

Experience with data preprocessing, feature engineering, and model evaluation techniques.

Understanding of cloud technologies and containerized deployments.

Excellent problem-solving and debugging skills.

Preferred Skills

Experience with MLOps, Docker, and Kubernetes.

Familiarity with NLP, computer vision, and deep learning techniques.

Knowledge of CI/CD pipelines and model monitoring tools.