Senior MLOps & Cloud Platform Engineer - Hybrid Atlanta

Honeywell

Atlanta (GA)

Ibrido

USD 130.000 - 190.000

Tempo pieno

7 giorni fa
Candidati tra i primi
Generatore di candidature

Trasforma questo annuncio in un colloquio — un curriculum e una lettera di presentazione creati in base a ciò questo datore di lavoro sta cercando.

Supera i filtri ATS

Vantaggi offerti da questo lavoro

Employer paid medical/dental/vision
401(k) match
Paid time off
Education assistance
Parental leave
Flexible spending accounts

Descrizione del lavoro

Honeywell is seeking a Senior Advanced Software Engineer to lead DevOps and SRE for AI/ML platforms, Databricks governance, and cloud initiatives from our Atlanta location on a hybrid schedule.

The role focuses on designing and operationalizing ML pipelines, enabling CI/CD practices, and managing Azure and GCP infrastructure. You will work closely with data scientists, software engineers, and product managers to deliver reliable AI solutions.

Competenze

  • 7+ years of DevOps/SRE experience.
  • 5+ years with Azure and GCP, infra automation with Terraform/Ansible, and Python scripting.
  • 5+ years building/managing CI/CD pipelines with GitHub Actions, Azure DevOps, Jenkins; 4+ years Docker/Kubernetes.

Mansioni

  • Lead DevOps/SRE activities for AI/ML platforms and cloud infra.
  • Design, implement, and optimize ML pipelines and CI/CD for AI/ML OPS.
  • Govern Databricks administration, data lake operations, and cloud platform governance.
  • Collaborate with software engineers, data scientists, and product managers to deliver reliable AI solutions.

Conoscenze

DevOps/SRE experience
Azure
GCP
Python
CI/CD
Docker
Kubernetes

Formazione

Bachelor's degree in CS/Engineering

Strumenti

Terraform
Ansible
GitHub Actions
Azure DevOps
Jenkins

Descrizione del lavoro

Honeywell is seeking a Senior Advanced Software Engineer to lead DevOps and SRE for AI/ML platforms, Databricks governance, and cloud initiatives from our Atlanta location on a hybrid schedule.

The role focuses on designing and operationalizing ML pipelines, enabling CI/CD practices, and managing Azure and GCP infrastructure. You will work closely with data scientists, software engineers, and product managers to deliver reliable AI solutions.

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