Machine Learning Infrastructure Engineer, Input and Interaction


Job Overview

Key Qualifications

  • 4+ years of SW development experience, including SW architecture design, reliability, and scaling
  • Proficiency in Python and C++ with solid object-oriented design fundamentals
  • Exposure to algorithms, AI/ML, or data science projects including evaluating algorithms on datasets
  • Experience developing and deploying automated algorithm evaluation and data pipelines on cloud services such as AWS, MS Azure, Google Cloud Platform, etc
  • Experience deploying and managing parallel computing tasks in cloud infrastructures with focus on scalability and performance
  • Understands and advocates principles of good software and system design
  • Able to communicate clearly and collaborate with cross-functional teams
  • Excellent problem solving and root cause analysis skills
  • Description

    In this role, you will write software to manage datasets, run algorithm pipelines at scale, and integrate with other algorithm teams to evaluate features end-to-end.Specifically, you will: * Develop and deploy scalable cloud infrastructure to run automated algorithm evaluation tasks on data* Develop software to analyze, annotate, and organize data at scale for integration with algorithm pipelines* Collaborate with cross-functional teams to leverage existing tools and frameworks and build on them* Integrate with other algorithm pipelines for end-to-end performance evaluations through KPIs * Generate comprehensive scorecards and automate analyses that help diagnose critical algorithm issues

    Education & Experience

    BS/MS/PhD in CS/CE/EECS or related field

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