Senior MLOps Engineer — AI Platform & Deployment

NRG Energy; Seattle (WA); Hybrid; USD 150,000 - 185,000; Full time

Benefits offered by this job

Paid holidays

Employee Discounts

Medical/dental/vision/life coverage

401(k) + Employer Match

Employee Resource Groups

Job summary

NRG Energy, through Vivint Smart Home, is seeking a Sr MLOps Engineer to build the model lifecycle and deployment infra for AI features in Seattle. The role requires hybrid in-office presence with a remote start transitioning to hybrid.

You will own model registries, versioning, and standardized workflows while collaborating with cross-functional teams to scale AI capabilities. Salary ranges reflect Seattle market norms.

Qualifications

• Experience building production ML platforms, model serving systems, or MLOps workflows.
• Familiarity with model registry, feature/data versioning (DVC), validation, deployment, rollback, and observability.
• Strong Python and cloud engineering skills.
• Experience with CI/CD, Git, infrastructure-as-code, and production monitoring.
• Ability to communicate tradeoffs clearly across engineering, data science, and product teams.

Responsibilities

• Build model registry, model serving, deployment, rollback, and CI/CD systems for production AI services.
• Own feature, dataset, model, and prompt versioning patterns across AI products.
• Standardize training, evaluation, release, monitoring, and operational workflows for AI teams.
• Improve reliability, cost efficiency, latency, and repeatability of AI launches.
• Create reusable platform patterns across AI features.
• Partner with engineering, data science, product, and operations teams to productionize AI capabilities at scale.

Skills

Python

Cloud engineering

CI/CD

Infrastructure as code

Observability

Communication across teams

Education

Bachelor’s in CS/SE/AI

Master’s in CS/SE/AI

Tools

GCP/AWS

Kubernetes

Vertex AI

SageMaker

MLflow

Job description

NRG Energy, through Vivint Smart Home, is seeking a Sr MLOps Engineer to build the model lifecycle and deployment infra for AI features in Seattle. The role requires hybrid in-office presence with a remote start transitioning to hybrid.

You will own model registries, versioning, and standardized workflows while collaborating with cross-functional teams to scale AI capabilities. Salary ranges reflect Seattle market norms.