ML/Ops Architect

Overview

On Site
$60 - $70
Accepts corp to corp applications
Contract - Independent
Contract - W2
Contract - 12 Month(s)

Skills

azure
mlops
ai ops
devsecops
devsec
devops

Job Details

Job Title: ML/Ops Architect
Location: San Antonio, TX - 4 days in a week onsite
Mode: Contract
Duration: 12 Months+
Job Description:
Must Have: MLOps, Azure Machine Learning
Position Summary
  • We are seeking an experienced and initiative-taking AI/MLOps Architect to join our Solution and Data Architecture team supporting the Data Science/AI Team. In this role, you will be pivotal in architecting robust AI/MLOps/LLMOps solutions on the Azure AI/ML platform. You will collaborate with cross-functional teams to streamline the AI/ML Azure Stack, ensuring our AI/ML initiatives are delivered with high quality and speed. You will be collaborating with team of MLOps Architects and Engineers supporting the Data Science & AI Team.
  • Key Responsibilities:
  • Architect Robust Azure AI/MLOps/LLMOps Solutions: To support the Data Science and AI Team to deliver high quality Data Science solutions to our business continuously.
  • Azure AI/ML Platform Orchestration: Provide thought leadership on all aspects of the Azure ML Platforms that host the ML models and deliver value to our clients within and outside of the organization.
  • Azure OpenAI Expertise: Have working knowledge of Azure OpenAI based AI/ML solutions to provide quick value to business.
  • Kubernetes Expertise: Provide thought leadership in the architecture and maintenance of the Azure AKS Clusters for the team to support AI/ML Initiatives.
  • Production Support: Be able to provide 24X7 production support for Azure ML models in case of issues/troubleshooting.
  • Promote DevSecOps Principles: Foster a DevSecOps culture across the Analytics & Innovation organization, ensuring security is integrated into the development process.
  • Collaboration: Work closely with data scientists, data engineers, and software developers to integrate and deploy machine learning models into production.
  • Security and Compliance: Ensure the security and compliance of data and infrastructure, adhering to industry best practices and regulatory requirements.
  • Documentation: Maintain comprehensive documentation of systems, processes, and workflows to facilitate knowledge sharing and collaboration.
  • Lifelong Learner: Exhibit an attitude of lifelong learning to keep up with the constant demands of keeping up instead of catching up in the field of AI/ML.
  • Requirements:
  • Education: Bachelor s Degree in Computer Science, Engineering, or a related field.
  • Experience: 7+ years of experience in DevOps, MLOps, or a related field.
  • Extensive Azure DevOps and AzureML experience.
  • Experience working on Linux based platforms for AI/ML Data Science solutions.
  • Experience working with Data Science and Machine Learning teams.
  • Technical Expertise:
  • Expert level proficiency in the Azure Cloud Platform and containerization technologies (Docker, Kubernetes).
  • Expert programming skills in Python, Bash, PowerShell, or other modern programming/scripting Languages.
  • Experience with infrastructure as code (Terraform, ARM or other IaC tools).
  • Tool/Platform Proficiency:
  • Familiarity with CI/CD tools (Jenkins, GitHub Actions, ADO Pipelines).
  • Knowledge of Azure Architecture with a focus on AI/ML Platforms.
  • Problem-Solving: Excellent problem-solving and analytical skills, with a
    focus on delivering practical and efficient solutions.
  • Preferred Experiences:
  • Advanced Analytics Tools: Experience with advanced analytics tools and methodologies, including monitoring and logging solutions (Azure Monitor, Prometheus, Grafana).
  • Agile Methodologies: Experience working in Agile development environments.
  • Communication: Strong verbal and written communication skills, capable of articulating complex technical concepts to both technical and non-technical stakeholders.
    Team Collaboration: A collaborative mindset with a record of working effectively within diverse teams.
  • Other Qualifications:
  • Microsoft Certified - Azure Data Scientist Associate OR AWS Certified
  • Machine Learning Specialty OR Google Certified Professional Machine Learning Engineer
  • Multiple Azure Certifications preferred in the field of Data, AI, ML or DevOps.
  • Terraform Certification preferred.
  • CKA Certification preferred.
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.