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Senior Machine Learning Engineer - Fraud and Risk

Posted 25 days agoViewed

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💎 Seniority level: Senior, Minimum of two years’ software development experience and two years’ experience using machine learning frameworks

💸 Salary: 180000.0 - 240000.0 USD per year

🔍 Industry: Ecommerce

🏢 Company: Bolt

⏳ Experience: Minimum of two years’ software development experience and two years’ experience using machine learning frameworks

Requirements:
  • Minimum of three years’ post-secondary education or relevant work experience.
  • At least two years’ software development experience with Python and SQL.
  • Two years’ experience using PyTorch, TensorFlow, or Spark ML for deploying NLP and deep learning models in cloud environments.
  • Thorough understanding of machine learning fundamentals and methodologies.
  • Experience building and deploying ML models in applied settings.
  • Strong understanding of scalable ML systems for online and offline applications.
  • Familiarity with best practices for ML model lifecycle management.
Responsibilities:
  • Build production ready machine learning models that power online commerce through Bolt.
  • Establish reusable frameworks for model building, deployment, and monitoring, with comprehensive logging and alerting.
  • Conduct data analysis to inform strategic growth and policy adoption.
  • Build machine learning infrastructure and data pipelines for live traffic.
  • Collaborate with Product Managers to track algorithmic performance and prioritize improvements.
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Related Jobs

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🔥 Senior Machine Learning Engineer - Fraud and Risk
Posted about 2 months ago

🧭 Full-Time

💸 180000.0 - 240000.0 USD per year

🔍 ECommerce

  • Minimum of three years’ post-secondary education or relevant work experience.
  • Minimum of two years’ software development experience with Python and SQL.
  • Minimum of two years’ experience using PyTorch, Tensorflow, Spark ML for building pipelines for NLP and deep learning in cloud environments.
  • Thorough understanding of machine learning fundamentals and methodologies.
  • Experience in building and deploying ML models in an applied setting.
  • Strong understanding of scalable ML systems for online and offline applications.
  • Familiarity with best practices for lifecycle management of ML models.

  • Build production-ready machine learning models for online commerce.
  • Establish reusable frameworks for model building, deployment, and monitoring.
  • Conduct data analysis to inform policy and strategic growth.
  • Develop machine learning infrastructure and data pipelines for live traffic.
  • Collaborate with Product Managers on algorithm performance KPIs and prioritization.
Posted about 2 months ago
Apply

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