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AI/ML Engineer with Site Reliability Engineering experience - Remote USA / Canada

ConnectedX, Inc.United States🇺🇸United StatesPosted 15 Jul 2026

Why This Role Stands Out

This remote role offers a fantastic opportunity to blend your AI/ML expertise with SRE best practices, allowing you to build and maintain robust machine learning systems. You'll thrive here if you possess strong Python skills, experience with Kubernetes and on-premises environments, and a passion for ensuring system reliability and performance. Apply now to contribute to innovative projects in a flexible, remote setting.

Quick Overview

Work Type
Remote
Level
Mid Senior

Job Description

Need only Permanent Residence with 10+ years of experience.

Job Title: Machine Learning Engineer (SRE Focus)

Location: Remote

Duration: Long Term (W2 Contract)

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

Skills

Docker
AWS
Machine Learning
Datadog
Kubernetes
Python

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