Machine Learning Engineer

at  Matrix Global

Toronto, Canada.
We seek a talented and experienced Machine Learning Engineer to join our team. As a Machine Learning Engineer, you will develop, deploy, and maintain machine learning models using Python and AWS SageMaker. You will collaborate with cross-functional teams to design and implement scalable and efficient machine-learning solutions to address complex business problems.

Responsibilities:

• Develop machine learning models for various applications, including but not limited to natural language processing, computer vision, and recommendation systems
• Preprocess and analyze large datasets to extract meaningful insights and features for model training
• Design and implement machine learning pipelines using Python libraries and frameworks such as TensorFlow, PyTorch, scikit-learn, and Keras
• Utilize AWS SageMaker for model development, training, deployment, and monitoring
• Optimize machine learning models for performance, scalability, and cost-effectiveness on AWS infrastructure
• Collaborate with software engineers to integrate machine learning models into production systems and applications
• Stay updated on the latest advancements and best practices in machine learning, cloud computing, and AWS services
• Mentor junior team members and contribute to a culture of continuous learning and innovation

Requirements:

• Bachelor’s or master’s degree in Computer Science, Engineering, Mathematics, Statistics, or related field
• 3+ Years of experience working as a Machine Learning Engineer or Data Scientist
• Proficiency in Python programming language and experience with relevant libraries and frameworks for machine learning
• Hands-on experience with AWS services, particularly AWS SageMaker, EC2, S3, IAM, and CloudWatch
• Strong understanding of machine learning algorithms and techniques, including supervised learning, unsupervised learning, and deep learning
• Experience with data preprocessing, feature engineering, model evaluation, and hyperparameter tuning
• Solid knowledge of OOP programming end experience
• Excellent problem-solving skills and ability to translate business requirements into machine-learning solutions
• Practical communication skills and ability to collaborate with cross-functional teams
• Strong attention to detail and commitment to delivering high-quality work
• Experience with containerization technologies such as Docker and orchestration tools like Kubernetes
• Strong communication and collaboration skills, with the ability to work effectively across cross-functional teams

Why Matrix

• Matrix is a global, dynamic, fast-growing technical consultancy leading technology services company with 13000 employees worldwide. Since its foundation in 2001, Matrix has made more travelers and acquisitions and has executed some of the largest and most significant. The company specializes in implementing and developing leading technologies, software solutions, and products. It provides its customers with infrastructure and consulting services, IT outsourcing, offshore, training and assimilation, and Ves as representatives for the world’s leading software vendors. With vast experience in private and public sectors, ranging from Finance, Telecom, Health, Hi-Tech, Education, Defense, and Security, Matrix’s customer base includes guest organizations in Israel and a steadily growing client base worldwide.
• We are comprised of talented, creative, and dedicated individuals who are passionate about delivering innovative solutions to the market. We source and foster the best talent and recognize that all employees’ contributions are integral to our company’s future.
• Matrix- success is based on a challenging work environment, competitive compensation and benefits, and rewarding career opportunities. We encourage a diverse work environment of sharing, learning, and ceding together. Come and join the winning team! You’ll be challenged and have fun in a highly respected organization. To Learn More, Visit: www.matrix-ifs.com

• Develop machine learning models for various applications, including but not limited to natural language processing, computer vision, and recommendation systems
• Preprocess and analyze large datasets to extract meaningful insights and features for model training
• Design and implement machine learning pipelines using Python libraries and frameworks such as TensorFlow, PyTorch, scikit-learn, and Keras
• Utilize AWS SageMaker for model development, training, deployment, and monitoring
• Optimize machine learning models for performance, scalability, and cost-effectiveness on AWS infrastructure
• Collaborate with software engineers to integrate machine learning models into production systems and applications
• Stay updated on the latest advancements and best practices in machine learning, cloud computing, and AWS services
• Mentor junior team members and contribute to a culture of continuous learning and innovatio