Software Engineer, MLOps - Hybrid

Welcome to the intersection of energy and home services. At NRG, we’re driven by our passion to create a smarter, cleaner and more connected future.

Vivint Smart Home, an NRG owned company, is a leading smart home company in the United States, dedicated to redefining the home experience with intelligent products and services. We find purpose in proactively protecting and keeping our customers connected to home, no matter where they are. Join the Smart Home team to create smarter, safer and more sustainable homes.

About This Role

Vivint, an NRG Company, is redefining home energy intelligence through data and AI to enable personalized comfort, energy efficiency, and demand-response optimization across millions of connected homes. We are seeking a Staff MLOps Engineer to design and maintain the tooling and infrastructure that enable data scientists to experiment rapidly and deploy models reliably. In this role you will build pipelines for training and inference, automate model lifecycle management, monitor performance and drift and ensure that our models operate securely and efficiently at scale.

• Design, implement and maintain MLOps services and pipelines that automate the training, testing, deployment and monitoring of machine learning models in production.
• Build and manage feature stores, data versioning systems and model registries to support reproducible experiments and continuous improvement of occupancy, HVAC and demand response models.
• Collaborate with data scientists, software engineers and Dev Ops teams to integrate models into existing systems, balancing performance, latency and resource constraints.
• Develop and enforce best practices for continuous integration and continuous delivery in machine learning projects, including automated testing, code reviews and model validation.
• Monitor the health of data and models in production, implement strategies for retraining and rollback and drive observability for model performance and drift.
• Optimize infrastructure for training and inference, leveraging cloud resources, containerization and orchestration frameworks to ensure scalability and cost efficiency.
• Provide mentorship to junior engineers and contribute to the development of MLOps standards and documentation across the organization.

• Bachelor’s degree in Computer Science, Data Science, Engineering or a related field and at least five years of experience in software engineering, data engineering or Dev Ops, with three or more years specifically in MLOps.
• Strong programming skills in languages such as Python and experience with machine learning frameworks (e.g., Tensor Flow, PyTorch, scikit‑learn).
• Proficiency with Dev Ops tools and practices, including Docker, Kubernetes and CI/CD pipelines, and familiarity with cloud platforms such as GCP, AWS or Azure.
• Experience with version control systems (Git) and infrastructure as code tools (Terraform) and with monitoring and observability tools.
• Solid understanding of machine learning workflows, including data preparation, model training, evaluation, deployment and monitoring.
• Excellent problem‑solving skills and ability to troubleshoot complex production issues.

• Experience building MLOps platforms for time series or IoT data, particularly in energy or smart home applications.
• Familiarity with feature stores, model interpretability and fairness in AI.
• Experience with big data technologies such as Apache Spark, Kafka or Hadoop.
• Previous experience leading or mentoring a team of engineers.

Role requires 4 days in office (Mon-Thurs)

If you reside in or intend to work remotely from California, Colorado, Connecticut, Hawaii, Illinois, Minnesota, Nevada, New York, Ohio, Washington D.C., Washington State or another state or locality with a pay transparency law, you may contact  for compensation information related to this position and other information as required by applicable law. Please include the job title in your request.

NRG Energy is committed to a drug and alcohol-free workplace. To the extent permitted by law and any applicable collective bargaining agreement, employees are subject to periodic random drug testing, and post-accident and reasonable suspicion drug and alcohol testing. EOE AA M/F/Vet/Disability. Level, Title and/or Salary may be adjusted based on the applicant's experience or skills.

Official description on file with Talent.