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DevOps Engineer (Data & AI Platform)

SimplePractice

Location
US
Workplace
Remote
Employment
Full Time
Salary
MXN 1,124,480–1,405,600
Apply on the employer’s site

Posted 1mo ago

The employer’s full description could not be read from their board. This is a summary of the posting — follow the apply link for the original.

Responsibilities

  • Build and operate infrastructure for data pipelines and AI/ML workloads
  • Develop and maintain CI/CD for application and model lifecycle
  • Manage Infrastructure as Code (Terraform) across environments
  • Support containerized workloads and orchestration (Docker, Kubernetes)
  • Partner with Machine Learning teams to productionize models
  • Implement monitoring, logging, and tracing for data flow and model performance
  • Improve reliability, scalability, and cost efficiency of data systems
  • Enforce security and access controls for data and infrastructure
  • Reduce operational overhead through automation and tooling

Requirements

  • 3+ years of experience in DevOps, SRE, or infrastructure engineering
  • End-to-End MLOps/LLMOps expertise deploying and maintaining ML/AI workflows
  • Strong cloud experience (AWS preferred)
  • Proficiency with Terraform (or similar IaC tools)
  • Experience with Docker and Kubernetes
  • Familiarity with CI/CD and Git-based workflows
  • Experience supporting data platforms (e.g., Airflow, Kafka, Spark, or similar)
  • Programming/scripting (Python, Bash, or similar)
  • Experience with observability tools and practices

Preferred

  • Experience with MLOps tooling (e.g., MLflow, SageMaker, Kubeflow)
  • Familiarity with LLM-based systems and AI observability (token usage tracking, prompt versioning) and evaluation loops
  • Experience with real-time or high-throughput data systems
  • Exposure to security and compliance requirements (e.g., SOC 2, HIPAA)
  • Experience with specific MLOps tooling (Outerbounds, SageMaker, Metaflow) and vector database

Skills

  • DevOps
  • SRE
  • MLOps
  • LLMOps
  • AWS
  • Terraform
  • Docker
  • Kubernetes
  • CI/CD
  • Git
  • Airflow
  • Kafka
  • Spark
  • Python
  • Bash
  • MLflow
  • SageMaker
  • Kubeflow
  • LLM
  • Outerbounds
  • Metaflow
  • Vector Database

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