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Sre

  • Sre job type Posted on: Oct 14, 2026
  • Sre experience level Openkyber
  • Sre employment type Atlanta, Georgia
  • Sre employment type Onsite
  • Sre salary Full-time

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Job Title :

Sre

Job Type :

Full-Time

Job Location :

Atlanta Georgia United States

Remote :

No

Jobcon Logo Job Description :

Need Only Machine Learning Engineer consultants. Please dont share AI/ML Engineer profiles.

Experience Level: 12+ years.

Job Title: Machine Learning Engineer (SRE Focus)

Location: Remote

Duration: Long Term

Job Summary: Experienced Machine Learning Engineer with a strong Site Reliability Engineering (SRE) mindset to join our team. The candidate will have hands-on experience maintaining applications on both Windows and Linux environments, managing on-premises servers, and working with Kubernetes clusters. This role requires solid Python programming skills, a good understanding of machine learning concepts, and practical knowledge of ML model deployment, monitoring, and debugging.

Key Responsibilities:

  • Maintain and support machine learning applications running on Windows and Linux servers in on-premises environments.
  • Manage and troubleshoot Kubernetes clusters hosting ML workloads.
  • Collaborate with data scientists and engineers to deploy machine learning models reliably and efficiently.
  • Implement and maintain monitoring and alerting solutions using DataDog to ensure system health and performance.
  • Debug and resolve issues in production environments using Python and monitoring tools.
  • Automate operational tasks to improve system reliability and scalability.
  • Ensure best practices in security, performance, and availability for ML applications.
  • Document system architecture, deployment processes, and troubleshooting guides.

Required Qualifications:

  • Proven experience working with Windows and Linux operating systems in production environments.
  • Hands-on experience managing on-premises servers and Kubernetes clusters and Docker containers
  • Strong proficiency in Python programming.
  • Solid understanding of machine learning concepts and workflows.
  • Experience with machine learning model deployment and lifecycle management.
  • Familiarity with monitoring and debugging tools, e.g. DataDog.
  • Ability to troubleshoot complex issues in distributed systems.
  • Experience with CI/CD pipelines for ML applications.
  • Familiarity with AWS cloud platforms
  • Background in Site Reliability Engineering or DevOps practices.
  • Strong problem-solving skills and attention to detail.
  • Excellent communication and collaboration skills.
  • We need an engineer who is also familiar with model development

For applications and inquiries,

Jobcon Logo Position Details

Posted:

Oct 14, 2026

Reference Number:

93401-38381

Employment:

Full-time

City:

Atlanta

Job Origin:

CIEPAL_ORGANIC_FEED

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Need Only Machine Learning Engineer consultants. Please dont share AI/ML Engineer profiles.

Experience Level: 12+ years.

Job Title: Machine Learning Engineer (SRE Focus)

Location: Remote

Duration: Long Term

Job Summary: Experienced Machine Learning Engineer with a strong Site Reliability Engineering (SRE) mindset to join our team. The candidate will have hands-on experience maintaining applications on both Windows and Linux environments, managing on-premises servers, and working with Kubernetes clusters. This role requires solid Python programming skills, a good understanding of machine learning concepts, and practical knowledge of ML model deployment, monitoring, and debugging.

Key Responsibilities:

  • Maintain and support machine learning applications running on Windows and Linux servers in on-premises environments.
  • Manage and troubleshoot Kubernetes clusters hosting ML workloads.
  • Collaborate with data scientists and engineers to deploy machine learning models reliably and efficiently.
  • Implement and maintain monitoring and alerting solutions using DataDog to ensure system health and performance.
  • Debug and resolve issues in production environments using Python and monitoring tools.
  • Automate operational tasks to improve system reliability and scalability.
  • Ensure best practices in security, performance, and availability for ML applications.
  • Document system architecture, deployment processes, and troubleshooting guides.

Required Qualifications:

  • Proven experience working with Windows and Linux operating systems in production environments.
  • Hands-on experience managing on-premises servers and Kubernetes clusters and Docker containers
  • Strong proficiency in Python programming.
  • Solid understanding of machine learning concepts and workflows.
  • Experience with machine learning model deployment and lifecycle management.
  • Familiarity with monitoring and debugging tools, e.g. DataDog.
  • Ability to troubleshoot complex issues in distributed systems.
  • Experience with CI/CD pipelines for ML applications.
  • Familiarity with AWS cloud platforms
  • Background in Site Reliability Engineering or DevOps practices.
  • Strong problem-solving skills and attention to detail.
  • Excellent communication and collaboration skills.
  • We need an engineer who is also familiar with model development

For applications and inquiries,

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