Sr Software Engineer, MLOps

NRG • Seattle, WA

4d • $150,000 - $185,000 • Hybrid

About The Position

Vivint Smart Home, an NRG-owned company, is seeking a Senior MLOps Engineer to build the model lifecycle, deployment, observability, and infrastructure foundations used by multiple production AI features, including recognition, AI Video Search, Multimodal AI, Agentic AI, and Energy AI. The role will help AI teams ship faster through shared, reliable platform primitives.

The engineer will build and maintain model registry, serving, deployment, rollback, and CI/CD systems for production AI services. They will establish versioning patterns for features, datasets, models, and prompts; standardize training, evaluation, release, monitoring, and operational workflows; and improve the reliability, cost efficiency, latency, and repeatability of AI launches. The position also involves creating reusable platform patterns and partnering with engineering, data science, product, and operations teams to productionize AI capabilities at scale.

The position requires in-office presence in Seattle, Washington, on a hybrid schedule: Monday through Thursday in the office and Friday working from home. It will start remotely and then transition to the hybrid schedule. The base salary range is $150,000 to $185,000. Actual salary may vary based on factors including location, experience, and performance. Additional compensation may include annual bonuses, short- and long-term incentives, and program-specific awards.

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, AI/ML, or a related technical field and at least 5 years of professional experience in software development, applied science, or ML engineering; or a master’s degree in one of those fields and at least 2 years of relevant professional experience.
• Experience building production ML platforms, model serving systems, or MLOps workflows.
• Strong Python and cloud engineering skills.
• Experience with CI/CD, Git, infrastructure-as-code, and production monitoring.
• Familiarity with model registry, feature/data versioning (DVC), validation, deployment, rollback, and observability.
• Ability to clearly communicate tradeoffs across engineering, data science, and product teams.

Nice To Haves

• Experience with GCP or AWS, Cloud Run, Kubernetes, Vertex AI, SageMaker, MLflow, or equivalent tools.
• Experience with AI services for computer vision, LLMs, multimodal models, or recommendation systems.
• Experience with data validation, dataset versioning, feature stores, or model quality monitoring.
• Experience optimizing cost, latency, reliability, and operational readiness for AI systems.
• Experience with IoT, edge AI, smart home, or distributed device environments.

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.

Benefits

• Paid holidays and flexible paid time away.
• Employee, friends, and family discounts.
• Medical, dental, vision, and life coverage, plus a 24/7 Medical Hotline.
• 401(k) with employer match.
• Employee Resource Groups.
• Potential eligibility for benefits including medical, vision, dental, 401(k), and flexible spending accounts.
• Additional rewards may include annual bonus, short- and long-term incentives, and program-specific awards.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior