Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
Senior Software Engineer, MLOps
Seattle, WA, US, 98104
Open 4 months, first seen by us 145 days ago- Pay
$150,000–185,000/year · BaseAnnual period assumed. Location-specific pay — pay source
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.
Read the full posting- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingWe 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.
Build model registry, model serving, deployment, rollback, and CI/CD systems for production AI services.
Build model registry, serving, deployment, rollback and CI/CD systems
Own feature, dataset, model and prompt versioning across AI products
Standardize training, evaluation, release and monitoring workflows for AI teams
Improve reliability, cost efficiency, latency and repeatability of AI launches
Create reusable platform patterns across AI features
From the employer’s posting
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
What you’ll bring
All qualificationsCore experience
- 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
Preferred experience
- 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
Qualification wording
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
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
Education & alternatives
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
- 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
Benefits in the posting
Full benefits wording- 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:
- 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.
From the employer’s posting.
Posting record
Report an errorOpen 4 monthsWe first saw this posting 145 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 13, 2026145 days ago
- Recorded sightings
- 683
- Last seen by us
- Nov 5, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 145
Up longer than most. Similar jobs usually come down between day 6 and day 70.
Well past NRG’s usual: its jobs come down by about day 34.
From 4,444 similar postings that came down, and 24 of NRG’s. Coming down is not always a hire.
NRG is hiring
2 open jobs
- Hiring has slowed
- Takes jobs down quickly
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- AWS
- GCP
- Kubernetes
- MLflow
- SageMaker
Where the posting names them
- 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
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
Your next step
Complete your application on careers.nrgenergy.com. The employer’s form will show what is required.
Applying through SAP SuccessFactors
- Images (.jpg) aren’t accepted as a resume.
Already applied? Track this application
About NRG
- People
- About 16,702 in 2025, up 7% from the year before.Annual report (SEC Form 10-K)
- Company
- Listed as NRG.
- H-1B visas
- 10 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
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.
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- Location & working pattern
Seattle, WA, US, 98104
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.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.