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Machine Learning Engineer - Applied / Product

Yobi· Engineering & Science
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Remote$180k - $275kFull-timePosted 11mo ago

About the role

ML Engineer focused on models, metrics, pipelines, systems, and services powering Yobi Applications products; 0→1 development with cross-functional collaboration to deliver holistic ML-powered products and drive product-market fit.

Responsibilities

  • Work on models, metrics, pipelines, systems, and services that power Yobi Applications products
  • Engage in large-scale 0→1 development
  • Collaborate with Product, core signals MLEs, and other stakeholders to build holistic ML-powered products
  • Contribute across the full stack of the ML pipeline (data orchestration, build systems, experiment tracking)
  • Drive product sense and decisions to achieve product-market fit and scalable impact

Qualifications

  • Experience working on impactful consumer-facing ML problems (e.g., recommender systems, personalization)
  • Ability to contribute to data orchestration, build systems, and experiment tracking; familiar with systems like Airflow, Bazel, Github CI/CD, Spark (not necessarily requiring prior experience with these exact tools)
  • Strong product sense and ability to advocate for product and implementation choices

Skills

Required:Machine learning problem solving (recommender systems / personalization)End-to-end ML pipeline developmentCross-functional collaboration

Benefits

  • Competitive Base Salary
  • Meaningful equity & financial upside - a real % of the company
  • Annual bonus target based on personal and company performance
  • Health, Dental, Vision
  • Unlimited PTO
  • 401k with company match %
  • Generous parental leave policy
Last updated Jul 29, 2026. Interested? Apply on the company site.

About Yobi

Democratize the AI Revolution

Foundation model to power AI Transformation. Anticipate consumer demand with Yobi’s flagship behavioral Machine Learning model.

Artificial IntelligenceMachine LearningBehavioral DataPersonalizationMarketing OptimizationMedia PerformanceRecommendationSearch

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