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ServiceNowPosted 1 month ago

Machine Learning Engineer, Agentic Application

$216–$139,700 year

On-siteMountain View Santa Clara County, California, United States

Full TimeEnterpriseInformation Technology And Services

Job Summary

Scale and optimize the Moveworks Generative AI product infrastructure to support hundreds of millions of users across multiple chat channels. Construct user-friendly interfaces for model customization and design scalable API abstractions for clients like MSTeams, Slack, and Web. Optimize the dialog engine for real-time multilingual translation with minimal memory footprint and low latency. Champion coding best practices, implement robust logging and tracing frameworks, and collaborate with cross-functional teams to drive scalability initiatives.

Required Qualifications

  • A strong foundation in computer science and software engineering
  • Expertise in building scalable systems
  • A deep understanding of clean, modular, and scalable API design
  • Ability to champion best coding practices
  • Ability to influence fellow engineers to uphold high standards of code quality and craftsmanship
  • Passion for optimizing systems and improving performance
  • Well-versed in tracing, logging, and metrics frameworks
  • Systematic approach to quickly identify and resolve latency bottlenecks
  • Systematic approach to quickly identify and resolve race conditions
  • Systematic approach to quickly identify and resolve throughput limitations
  • Ability to independently research new requirements
  • Ability to develop innovative solutions
  • Thrive in an environment of fast-paced coding and execution
  • Embrace rapid iterations to deliver results
  • Strong communication skills
  • Ability to effectively articulate rationales and design approaches
  • Cross-functional awareness
  • Ability to collaborate seamlessly with various teams
  • Bachelor's degree or higher in computer science or a related field
  • 2+ years of professional development experience
  • Experience specifically in building systems at scale

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