Senior Machine Learning Engineer, Developer Advocacy
New
J
JobgetherSecurity & IT
CanadaFull-TimeSenior
Salary$164,490 CAD – $197,389 CAD
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Job Details
- Required Skills
- Machine LearningTypeScriptData scienceGogRPCDistributed Systems
Requirements
- Proven experience building recommendation, ranking, search, matching, propensity, or next-best-action systems.
- Strong understanding of personalization techniques and ability to start with simple, explainable approaches.
- Experience independently building, validating, monitoring, and improving machine learning models used in production.
- Ability to work effectively within version-controlled codebases and collaborate with software engineering teams.
- Strong product mindset with the ability to turn ambiguous goals into measurable experiments and iterative improvements.
- Experience working with behavioral data, SaaS telemetry, customer data, or large-scale analytics environments.
- Strong analytical, problem-solving, and communication skills.
- Ability to explain technical concepts, modeling choices, and results clearly to diverse audiences.
- Experience with distributed systems and technologies such as HTTP, gRPC, streaming architectures, Go, or TypeScript is beneficial.
Responsibilities
- 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.
- 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.
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