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Platform Engineer

  • Platform Engineer job type Posted on: Oct 12, 2026
  • Platform Engineer experience level Openkyber
  • Platform Engineer employment type Atlanta, Georgia
  • Platform Engineer employment type Onsite
  • Platform Engineer salary Full-time
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Job Title :

Platform Engineer

Job Type :

Full-Time

Job Location :

Atlanta Georgia United States

Remote :

No

Jobcon Logo Job Description :

Job Title: Platform Engineer
Location: Tampa, FL, Raleigh, NC, Durham, NC, Orlando, FL, Columbia, SC, Atlanta, GA, Charlotte, NC.

We are seeking a Senior AI/ML Platform Engineer to build enterprise-scale Machine Learning platforms supporting model development, deployment, monitoring, and governance.

The ideal candidate should have strong expertise in MLOps, LLMOps, cloud-native AI platforms, Feature Stores, and scalable ML infrastructure.

Key Responsibilities:
  • Design enterprise AI/ML platforms and reusable ML pipelines.
  • Build scalable MLOps and LLMOps workflows.
  • Develop model training and deployment pipelines.
  • Implement Feature Stores and Model Registry.
  • Build CI/CD pipelines for ML applications.
  • Monitor model performance, drift, and data quality.
  • Develop REST APIs for model serving.
  • Deploy workloads on Azure, AWS, or Google Cloud Platform.
  • Implement Responsible AI and model governance.
  • Collaborate with Data Science and DevOps teams.
Required Skills: Python, SQL, Machine Learning, MLOps, LLMOps, MLflow, Kubeflow, Feature Store, Model Registry, Docker, Kubernetes, FastAPI, REST APIs, Git, Azure, AWS, Google Cloud Platform, CI/CD.
Preferred Skills: SageMaker, Azure ML, Vertex AI, Ray, Airflow, Dataiku.

For applications and inquiries,

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Jobcon Logo Position Details

Posted:

Oct 12, 2026

Reference Number:

90159-38381

Employment:

Full-time

City:

Atlanta

Job Origin:

CIEPAL_ORGANIC_FEED

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Job Title: Platform Engineer
Location: Tampa, FL, Raleigh, NC, Durham, NC, Orlando, FL, Columbia, SC, Atlanta, GA, Charlotte, NC.

We are seeking a Senior AI/ML Platform Engineer to build enterprise-scale Machine Learning platforms supporting model development, deployment, monitoring, and governance.

The ideal candidate should have strong expertise in MLOps, LLMOps, cloud-native AI platforms, Feature Stores, and scalable ML infrastructure.

Key Responsibilities:
  • Design enterprise AI/ML platforms and reusable ML pipelines.
  • Build scalable MLOps and LLMOps workflows.
  • Develop model training and deployment pipelines.
  • Implement Feature Stores and Model Registry.
  • Build CI/CD pipelines for ML applications.
  • Monitor model performance, drift, and data quality.
  • Develop REST APIs for model serving.
  • Deploy workloads on Azure, AWS, or Google Cloud Platform.
  • Implement Responsible AI and model governance.
  • Collaborate with Data Science and DevOps teams.
Required Skills: Python, SQL, Machine Learning, MLOps, LLMOps, MLflow, Kubeflow, Feature Store, Model Registry, Docker, Kubernetes, FastAPI, REST APIs, Git, Azure, AWS, Google Cloud Platform, CI/CD.
Preferred Skills: SageMaker, Azure ML, Vertex AI, Ray, Airflow, Dataiku.

For applications and inquiries,

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