Senior Machine Learning Engineer, Ranking

Canada
Remote
Posted Oct 12, 2026
1 position

$227,108–$282,076 / year

Opens an external site

Employment type: Full-time
Experience level: Mid-level · 5+ years
Minimum education: Bachelor’s degree
Posting language: English
Working hours: 40 hours per week

Job summary

You will take end-to-end ownership of machine learning ranking models, including data pipelines, feature engineering, and production deployment. You will also collaborate with a distributed team to develop methodologies that improve content discovery and user engagement.

Job details

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior Machine Learning Engineer, Ranking based in Canada. We are seeking an experienced Machine Learning Engineer to advance recommendation and ranking systems that help users discover relevant content across a large-scale knowledge-sharing platform. In this remote role, you will take ownership of high-impact ranking models powering personalized feeds and digest emails. You will work across the full machine learning lifecycle, from data pipelines and feature engineering to model training and production deployment. Collaborating with a talented, distributed engineering team, you will experiment with modern machine learning techniques and develop methodologies that can support future product innovations. The environment values autonomy, continuous learning, technical excellence, and thoughtful experimentation. This is an opportunity to make a meaningful impact on how millions of users discover information and connect with knowledge. \n Accountabilities Improve and evolve existing machine learning ranking models by applying strong software engineering skills and advanced machine learning techniques. Take end-to-end ownership of machine learning systems, including data pipelines, candidate extraction, feature engineering, model training, evaluation, and integration into production environments. Advance second-stage ranking models that power personalized feeds and digest emails, improving the relevance and quality of content recommendations. Identify opportunities to apply machine learning across different product experiences and develop solutions that improve content discovery and user engagement. Collaborate with other machine learning engineers to design, implement, and optimize algorithms and systems efficiently. Develop reusable methodologies, technical approaches, and engineering practices that enable other developers to build on top of existing ranking systems. Experiment with new modeling techniques, evaluate results, and continuously improve system performance and reliability. Contribute to a collaborative engineering culture focused on learning, innovation, knowledge sharing, and continuous improvement. Requirements: At least 3 years of professional experience developing recommendation systems or ranking models. Strong understanding of the mathematical foundations underlying machine learning algorithms. Previous experience designing, building, and deploying end-to-end machine learning systems in production. A bachelor's, master's, or doctoral degree in Computer Science, Engineering, or a related technical discipline. Strong communication and interpersonal skills, with the ability to collaborate effectively in a distributed engineering team. Availability for meetings and real-time collaboration during the team's coordination hours, Monday through Friday, from 9:00 a.m. to 3:00 p.m. Pacific Time. Preferred qualifications: At least 5 years of experience writing production-quality Python or C++ code. Experience with generative recommendation systems and modern recommendation modeling techniques. Familiarity with user behavior modeling, user sequence modeling, transformers, or long-sequence modeling applied to ranking. Experience leading large-scale technical projects involving multiple engineers. A flexible, positive, and collaborative approach to teamwork, along with strong interpersonal skills. Interest in improving how people discover and share knowledge through technology. Benefits: Medical, dental, and vision coverage, depending on the country of employment. Equity refreshers and, in eligible countries, access to a flexible equity program that may allow a portion of equity compensation to be received as cash. Remote work reimbursement. Paid time off. Employee assistance programs. Additional benefits that vary according to the country of employment. Competitive compensation for candidates based in Canada: Toronto and Vancouver: CAD $243,330–$282,076, plus equity and benefits. Other Canadian locations: CAD $227,108–$263,271, plus equity and benefits. \n How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1

What you’ll do

Requirements

Candidates must have at least 3 years of professional experience in recommendation systems or ranking models and a strong understanding of machine learning mathematics. A degree in Computer Science, Engineering, or a related technical field is required.