Senior MLOps Engineer

Our client is looking to fill the role of Senior MLOps Engineer (Google Cloud Platform). This position will be remote and will require occasional travel to Nashville, TN.We are seeking a Senior MLOps Engineer with extensive experience in Google Cloud Platform (Google Cloud Platform) infrastructure to join our team. The primary focus of this role is on applied ML engineering, specifically around Google Cloud Platform infrastructure and Vertex AI, to drive machine learning operations (MLOps) at scale. The ideal candidate will play a key role in building and optimizing ML pipelines, managing cloud infrastructure, and ensuring robust security and deployment using modern cloud tools.

• Salary range: 150k-170k base + Full Benefits

Responsibilities:

• Design, build, and manage MLOps infrastructure on Google Cloud Platform, with a strong emphasis on Vertex AI for model development, training, and deployment.
• Implement and manage Google Cloud Platform Infrastructure using Terraform to automate provisioning and configuration management.
• Develop and maintain robust IAM (Identity and Access Management) configurations to ensure secure access to cloud resources.
• Contribute to continuous integration and continuous deployment (CI/CD) processes to streamline model updates and deployment.
• Set up data integrations with Google Cloud Composer pipelines
• Collaborate with data scientists and applied engineers to integrate ML models into scalable, production-level pipelines.
• Optimize cloud infrastructure for performance, scalability, and cost efficiency.
• Troubleshoot and resolve issues related to cloud infrastructure, orchestration, and ML pipeline performance.

Qualifications:

• Proven experience with Google Cloud Platform (Google Cloud Platform), including Vertex AI, Terraform, Composer, and Kubeflow.
• Strong background in infrastructure management, automation, and orchestration on Google Cloud Platform.
• Solid understanding of IAM and security best practices within Google Cloud Platform environments.
• Hands-on experience with MLOps, specifically around model deployment and scaling in cloud environments.
• Experience in healthcare or familiarity with healthcare data and regulations (nice to have, but not required).
• Excellent problem-solving skills and the ability to work independently.
• Strong communication skills to collaborate with cross-functional teams.

If you meet the required qualifications and are interested in this role, please apply today.

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