Overview
On Site
$50+
Contract - W2
Skills
Proficiency in Python and shell scripting
with a focus on build automation and deployment processes Strong knowledge of cloud platforms (particularly AWS) and infrastructure-as-code principles Familiarity with artifact repositories (e.g.
Artifactory) and version control systems (e.g.
Git) Understanding of AI/ML development workflows and the specific infrastructure requirements for deploying AI/ML models Extensive experience in DevOps practices
CI/CD pipelines
and containerization technologies (Docker
Kubernetes) This position will play a crucial role in modernizing our build and deployment infrastructure to better support AI/ML development in our IoT services. The contractor will replace outdated build tools with a more flexible
Python-friendly system that aligns with our existing software deployment practices
enabling efficient development and deployment of AI/ML projectstoAWS.
Job Details
Position: MLOps Engineer
Client - Verizon,
Irving, TX
Main focus
ML Engineering/MLOps
Data Engineering
Required Skill Set:
Proficiency in Python and shell scripting, with a focus on build automation and deployment processes
Strong knowledge of cloud platforms (particularly AWS) and infrastructure-as-code principles
Familiarity with artifact repositories (e.g., Artifactory) and version control systems (e.g., Git)
Understanding of AI/ML development workflows and the specific infrastructure requirements for deploying AI/ML models
Extensive experience in DevOps practices, CI/CD pipelines, and containerization technologies (Docker, Kubernetes)
This position will play a crucial role in modernizing our build and deployment infrastructure to better support AI/ML development in our IoT services. The contractor will replace outdated build tools with a more flexible, Python-friendly system that aligns with our existing software deployment practices, enabling efficient development and deployment of AI/ML projects to AWS.
Required Skill Set:
Proficiency in Python and shell scripting, with a focus on build automation and deployment processes
Strong knowledge of cloud platforms (particularly AWS) and infrastructure-as-code principles
Familiarity with artifact repositories (e.g., Artifactory) and version control systems (e.g., Git)
Understanding of AI/ML development workflows and the specific infrastructure requirements for deploying AI/ML models
Extensive experience in DevOps practices, CI/CD pipelines, and containerization technologies (Docker, Kubernetes)
This position will play a crucial role in modernizing our build and deployment infrastructure to better support AI/ML development in our IoT services. The contractor will replace outdated build tools with a more flexible, Python-friendly system that aligns with our existing software deployment practices, enabling efficient development and deployment of AI/ML projects to AWS.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.