Sr Software Engineer, MLOps
At a glance
Senior ML Platform & Ops role at NRG Energy. Seattle · $150,000–$185,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Build the registry, serving, release, rollback, and CI/CD systems that put models into production
- Set consistent ways to version features, datasets, models, and prompts across AI products
- Give AI teams repeatable steps for training, evaluation, release, monitoring, and operations
- Improve launch reliability, cost, latency, and repeatability, while creating platform patterns teams can reuse
- Work with engineering, data science, product, and operations to bring AI capabilities into production
What you bring
- A related technical bachelor's degree plus five years in software development, applied science, or ML engineering, or a master's plus two years
- Hands-on experience building production ML platforms, model-serving systems, or MLOps workflows
- Strong Python and cloud engineering skills, with experience in CI/CD, Git, infrastructure-as-code, and production monitoring
- Clear communication of technical tradeoffs across engineering, data science, and product teams
Who this fits
This senior engineering role suits someone who builds production ML infrastructure and works across technical and product teams. The job starts remotely, then requires a hybrid schedule in Seattle, with office attendance Monday through Thursday and work from home on Friday.
From the employer
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
We are seeking a Sr 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 ship faster with shared, reliable platform primitives. In this role, you will be responsible for:
- 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.
Required Qualifications:
- Bachelor’s degree in Computer Science, Software Engineering, AI/ML, or a related technical field, and 5+ years of professional experience in software development, applied science, or ML engineering; or
- Master’s degree in Computer Science, Software Engineering, AI/ML, or a related technical field, and 2+ years of professional experience in software development, applied science, or ML engineering
- 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)[CH1] , validation, deployment, rollback, and observability
- Ability to communicate tradeoffs clearly across engineering, data science, and product teams
Preferred Qualifications:
- Experience with GCP/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
Working at Vivint:
Learn about the Vivint Culture and why it’s a great place to grow your career!
Here are some highlighted perks you should ask us about:
• Paid holidays and flexible paid time away
• Employee/Friends/Family Discounts
• Medical/dental/vision/life coverage & 24/7 Medical Hotline
• 401(k) + Employer Match
• Employee Resource Groups
Job Functions:
Position requires in-office presence in Seattle, WA on a hybrid schedule for Monday, Tuesday, Wednesday, and Thursday with a work from home day on Friday. The position will start remote and then will move into the hybrid schedule.
The base salary range for this position is: $150K to $185K* *The base salary range above represents the low and high end of the salary range for this position. Actual salaries will vary based on several factors including but not limited to location, experience, and performance. The range listed is just one component of the total compensation package for employees. Other rewards may include annual bonus, short- and long-term incentives, and program-specific awards. In addition the position may be eligible to participate in the benefits program which include, but are not limited to, medical, vision, dental, 401K, and flexible spending accounts.
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/Protected Veteran Status/Disability. Level, Title and/or Salary may be adjusted based on the applicant's experience or skills.
EEO is the Law Poster (The poster can be found at http://www.eeoc.gov/employers/upload/poster_screen_reader_optimized.pdf)
Official description on file with Talent.