Machine Learning Engineer (Canada)

Overview

Jobright is an AI-powered career search platform focused on making the job hunt faster, more tailored, and easier to navigate. The company is hiring a Machine Learning Engineer to build the models behind resume understanding, job matching, and career guidance for users.

Why you may want to join

• You will work on models that influence real career outcomes for a large number of job seekers, rather than only chasing benchmark scores.
• You will own the full machine learning workflow, including data preparation, training, deployment, monitoring, and ongoing improvements.
• You will collaborate with engineers and researchers who value strong model performance, sound system architecture, and rapid delivery.
• You will be part of a team with substantial ML infrastructure, allowing you to focus more on modeling and less on support code.

Responsibilities

• Develop, train, and launch machine learning models that support core platform features such as matching, ranking, and recommendations.
• Create and maintain training pipelines, feature stores, and evaluation systems that enable quick experimentation and reliable measurement.
• Work with product, engineering, and applied AI colleagues to turn unclear product needs into concrete modeling tasks and delivered features.
• Track model behavior in production, investigate performance drops, and apply insights to future model iterations.

Requirements

• 1 to 3 years of experience in machine learning, data science, or a closely related technical area.
• Ability to communicate model decisions, tradeoffs, and outcomes clearly to both technical and non-technical audiences.
• Strong understanding of classical machine learning and modern deep learning, including how to train, evaluate, and deploy models at scale.
• Preferred: experience from an internship or industry role in ML engineering, applied research, or data science within a tech or AI-driven organization.
• Preferred: experience delivering production ML solutions in fast-changing environments where data, priorities, and requirements evolve often.
• Preferred: practical experience with Python, PyTorch or TensorFlow, distributed training and inference, MLOps tools, and SQL-based data systems.

Eligibility

This role suits an early-career ML professional who can work on-site in Canada and collaborate across technical and non-technical teams.

Additional Information

The position is full-time and on-site. No salary, stipend, number of openings, start date, or application deadline was specified in the source.