Senior MLOps Engineer: AI Production Platform Lead

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

Benefits offered by this job

Paid holidays

Medical/dental/vision coverage

401(k) + Employer Match

Employee Resource Groups

Job summary

Vivint Smart Home is seeking a Sr MLOps Engineer to build the model lifecycle, deployment, observability, and infrastructure foundations used by multiple AI features. You will own versioning, CI/CD, and platform patterns to productionize AI at scale, collaborating with engineering, data science, and product teams.

The role requires in-office presence in Seattle on a hybrid schedule, with potential remote start and transition to hybrid.

Qualifications

• Bachelor’s or Master’s degree in a technical field with relevant ML/software experience
• Experience building production ML platforms or MLOps workflows
• Strong Python and cloud engineering skills
• Experience with CI/CD, Git, IaC, and production monitoring
• Familiarity with model registry, data/versioning, validation, deployment, rollback, and observability
• Ability to communicate tradeoffs across teams

Responsibilities

• Build model registry, serving, deployment, rollback, and CI/CD systems for production AI services
• Own feature, dataset, model, and prompt versioning
• 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
• Collaborate with engineering, data science, product, and operations teams to productionize AI capabilities at scale

Skills

Python

Cloud engineering

CI/CD

Git

Infrastructure as code

Monitoring

Model registry

Data/versioning (DVC)

Validation

Observability

Education

Bachelor’s degree in CS/SE/AI/ML

Master’s degree in CS/SE/AI/ML

Tools

GCP

AWS

Kubernetes

Cloud Run

Vertex AI

SageMaker

MLflow

Job description

Vivint Smart Home is seeking a Sr MLOps Engineer to build the model lifecycle, deployment, observability, and infrastructure foundations used by multiple AI features. You will own versioning, CI/CD, and platform patterns to productionize AI at scale, collaborating with engineering, data science, and product teams.

The role requires in-office presence in Seattle on a hybrid schedule, with potential remote start and transition to hybrid.