Senior Machine Learning Engineer, Ranking

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.