(can) Senior, Data Scientist - Ml Ops Engineering

Walmart

Mississauga, ON, Canada
Base: $91 900,00 - $126 390,00; bonus/equity: not ...
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Ml model deployment lifecycle management
Cloud infrastructure setup hosting
Ci/cd pipelines for ml
** Walmart is seeking a Senior Data Scientist specializing in ML Ops Engineering to enhance their data-driven culture by developing scalable machine learning platforms and deployment frameworks. The ideal candidate should have a strong background in ML systems engineering, cloud infrastructure, and cross-functional collaboration to support AI initiatives across the organization. **

Job Summary

  • This role drives a data-driven culture by leveraging diverse data sources to understand customer behavior, improve operational efficiencies, and provide actionable insights for smarter decision-making.
  • We are seeking an ML Ops Engineering expert to design, build, and operationalize scalable machine learning platforms and deployment frameworks that power AI initiatives across the organization.
  • Working closely with Data Science, Engineering, DevOps, and Security teams, this individual will ensure that ML solutions and associated applications are scalable, secure, compliant, and aligned with enterprise standards.

Matching Summary

Match Score: 75

** Walmart is seeking a Senior Data Scientist specializing in ML Ops Engineering to enhance their data-driven culture by developing scalable machine learning platforms and deployment frameworks. The ideal candidate should have a strong background in ML systems engineering, cloud infrastructure, and cross-functional collaboration to support AI initiatives across the organization. **

Salary

Base: $91 900,00 - $126 390,00; Bonus/Equity: Not specified; Benefits: Not specified

Skills & Requirements

Must-have

  • ML model deployment lifecycle management
  • Cloud infrastructure setup hosting
  • CI/CD pipelines for ML
  • Containerization orchestration
  • Security governance compliance processes
  • Cross-functional collaboration

Nice-to-have

  • Data-driven culture
  • Entrepreneurial business-focused team
  • Growth mindset curiosity
  • Continuous improvements digital tools

Key Requirements

  • ML model deployment and lifecycle management
  • Cloud infrastructure setup and application hosting
  • CI/CD pipelines for ML and application workflows
  • Containerization and orchestration
  • Security, governance, and SSP / InfoSec compliance processes
  • Cross-functional collaboration

Work Rights

Not specified

Tailored Resume

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