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Applied Scientist II: ML for Scalable Cloud Automation

Amazon

Toronto

On-site

CAD 90,000 - 120,000

Full time

7 days ago
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Job summary

A leading technology company in Toronto is seeking an Applied Scientist II to contribute to the automation of cloud infrastructure through advanced machine learning and statistical algorithms. Responsibilities include designing scalable models for forecasting and optimization and collaborating with engineering teams to implement solutions. Candidates should have a strong background in programming and experience in building complex models for business applications. This role offers significant impact in streamlining operations for thousands of developers across multiple functions.

Qualifications

  • 3+ years of experience building models for business applications.
  • Experience in patents or publications at top-tier conferences.
  • Experience in algorithms and data structures, data mining, and high-performance computing.

Responsibilities

  • Design, implement, and evaluate advanced statistical and machine learning models.
  • Collaborate closely with engineering teams to integrate models into production systems.
  • Conduct rigorous experimentation and A/B testing to measure business impact.

Skills

Building models for business applications
Programming in Java, C++, Python
Algorithms and data structures
Numerical optimization

Education

PhD or Master's degree in CS, CE, ML or related field

Tools

Unix/Linux
Job description
A leading technology company in Toronto is seeking an Applied Scientist II to contribute to the automation of cloud infrastructure through advanced machine learning and statistical algorithms. Responsibilities include designing scalable models for forecasting and optimization and collaborating with engineering teams to implement solutions. Candidates should have a strong background in programming and experience in building complex models for business applications. This role offers significant impact in streamlining operations for thousands of developers across multiple functions.
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