Senior Machine Learning Engineer, Ranking

Jobgether SRL; Canada; Sur place; CAD 243 000 - 282 000; Plein temps

Avantages offerts par ce poste

Medical, dental, and vision coverage

Remote work reimbursement

Equity program

Paid time off

Employee assistance programs

Additional country-specific benefits

Résumé du poste

Jobgether SRL is seeking a Senior Machine Learning Engineer, Ranking, to advance recommendation and ranking systems across a large-scale knowledge-sharing platform. This remote role in Canada leads end-to-end ML pipelines, feature engineering, model training and production deployment, collaborating with a distributed team.

You will improve second-stage ranking models for personalized feeds and digests, apply modern ML techniques, and drive reliable, scalable solutions that impact millions of

Qualifications

• 3+ years of experience developing recommendation or ranking models.
• Strong mathematical foundation for ML algorithms.
• Experience building end-to-end ML systems in production.
• Bachelor’s/Master’s/PhD in CS, Engineering, or related field.

Responsabilités

• Improve and evolve ranking models with strong software engineering.
• Own ML systems from data pipelines to production deployment.
• Advance second-stage ranking for personalized feeds and digests.
• Collaborate with distributed ML engineers to design and optimize algorithms.

Connaissances

Recommendation systems

Ranking models

Distributed teamwork

Strong mathematical foundations

Data pipelines

Formation

Bachelors in CS/Engineering or related

Masters/PhD in related field (optional)

Outils

Python

C++

Description du poste

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.

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.

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.