Senior Machine Learning Engineer, Developer Advocacy - jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Machine Learning Engineer, Developer Advocacy based in Canada.

This role offers the opportunity to build advanced machine learning solutions that improve how users discover and engage with product experiences. You will lead the evolution of a personalized recommendation system, transforming user behavior and content insights into intelligent learning journeys. The position combines applied machine learning, product experimentation, and engineering collaboration within a fully remote global environment. You will own the development, deployment, and optimization of recommendation models while helping define the future of personalized user experiences. The ideal candidate will enjoy solving complex data challenges, working across disciplines, and translating research into measurable product improvements. You will collaborate with engineering, analytics, product, and developer-focused teams to create impactful AI-driven experiences at scale.

Accountabilities:

As a Senior Machine Learning Engineer, Developer Advocacy, you will take ownership of building and improving intelligent recommendation systems that help users achieve better outcomes. You will combine machine learning expertise, product thinking, and strong communication skills to deliver scalable solutions and measurable improvements.

• Lead the evolution of personalized recommendation systems by developing ranking, sequencing, candidate selection, and next-best-action approaches.
• Build, deploy, monitor, and continuously improve machine learning models powering recommendation experiences.
• Own model development workflows, including training, validation, versioning, deployment, and performance monitoring.
• Define recommendation quality metrics and establish evaluation frameworks across offline, online, and longitudinal measurements.
• Develop and maintain feature pipelines, monitoring strategies, and supporting model infrastructure.
• Deliver incremental improvements by leveraging existing data and infrastructure while identifying opportunities for future enhancements.
• Collaborate with software engineers to productionize machine learning models and integrate them safely into product systems.
• Partner with analytics teams on instrumentation, data quality, dashboards, experimentation, and performance analysis.
• Work closely with product, engineering, developer-focused, documentation, and go-to-market teams to translate business needs into measurable hypotheses.
• Communicate modeling decisions, trade-offs, uncertainty, and results clearly to both technical and non-technical stakeholders.
• Contribute to responsible AI practices, including privacy, fairness, explainability, and transparent personalization.