ERTH Corporation is looking for a hands-on, versatile machine learning engineer to join our team as we begin our journey of integrating machine learning (ML) into our software development practices. This is a foundational role that will help shape ERTH’s ML capabilities, from identifying viable use cases to building and deploying production-ready models. This role is remote, but monthly in person attendance is required for meetings in Toronto.

SKILLS AND QUALIFICATIONS

· Bachelor’s degree in computer science, engineering, mathematics, or related field
· 2+ years of experience in software development, with over one year of experience focused on machine learning projects
· Extensive math and technical skills, with a deep understanding of data modeling
· In-depth knowledge of machine learning frameworks
· Familiarity with Python, Java, and R
· Excellent communication and collaboration skills
· Impeccable analytical and problem-solving skills
· Innovative mind with a passion for continuous learning
ERTH is an equal opportunity employer. Accommodations are available for all parts of the recruitment process under the Human Rights Code and the Accessibility for Ontarians with Disabilities Act. Applicants must make their needs known in advance.
Interested and qualified candidates are invited to apply, in confidence, by submitting a resume, stating qualifications and work experience by Thursday July 31, 2025 to human_resources@erthcorp.com. Only resumes submitted to the email address provided will be considered.
We thank all applicants for their interest, however, only those selected for an interview will be contacted.
Job Types: Full-time, Permanent

Benefits:

• Company events
• Dental care
• Disability insurance
• Employee assistance program
• Extended health care
• Life insurance
• Paid time off
• Vision care
• Work from home

Work Location: Remote
Application deadline: 2025-07-3

· Collaborate with software developers and stakeholders to identify machine learning use cases
· Design and develop machine learning models, ensuring they are maintainable and secure for tasks such as prediction, anomaly detection, recommendation and automation
· Solve complex problems with multilayered data sets, and optimize machine learning libraries and frameworks
· Monitor model performance and implement strategies for continuous improvement
· Stay up to date with developments in machine learning and contribute to best practices, tooling, and frameworks to support future ML initiatives
· Support upskilling and knowledge-sharing across the development team