ML Infrastructure Engineer
San Francisco, CA
- Pay
Multiple pay statements — pay source
Familiarity with feature stores, model registries, or centralized metadata systems (i.e. MLFlow) Senior ML Engineer Base Salary- $190,000-$210,000 Staff ML Engineer Base Salary- $245,000-$250,000.
Senior ML Engineer Base Salary- $190,000-$210,000 Staff ML Engineer Base Salary- $245,000-$250,000. Salary
Salary 190,000 – 250,000 USD per year **At this time, Gridware is unable to provide visa sponsorship or immigration support for this role. We’re only able to consider candidates who are currently authorized to work in the country of employment without visa sponsorship now or in the future.**
Read the full posting- Work setup
- Unconfirmed
- Employment
Full-time — employment source
Employment type Full-Time
Read the full posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
**At this time, Gridware is unable to provide visa sponsorship or immigration support for this role. We’re only able to consider candidates who are currently authorized to work in the country of employment without visa sponsorship now or in the future.**
Read the full posting
What you’ll work on
Full postingAs a Senior ML Infrastructure Engineer, you will work directly in the Automation org with the core ML, Ops, and Analytics teams to help improve and build out the infrastructure around model deployment and monitoring.
Design, build, and maintain the infrastructure, tooling, and workflows that enable reliable, scalable deployment of ML models to production.
Develop monitoring and observability systems to track model performance, data drift, data quality, and overall system health.
Create and maintain end-to-end testing frameworks and simulation environments to validate models and pipelines prior to deployment.
From the employer’s posting
As a Senior ML Infrastructure Engineer, you will work directly in the Automation org with the core ML, Ops, and Analytics teams to help improve and build out the infrastructure around model deployment and monitoring. This role is essential to helping scale out the amount of time saving’s Gridware brings to customers.
Responsibilities Design, build, and maintain the infrastructure, tooling, and workflows that enable reliable, scalable deployment of ML models to production. Develop monitoring and observability systems to track model performance, data drift, data quality, and overall system health.
Design, build, and maintain the infrastructure, tooling, and workflows that enable reliable, scalable deployment of ML models to production. Develop monitoring and observability systems to track model performance, data drift, data quality, and overall system health. Create and maintain end-to-end testing frameworks and simulation environments to validate models and pipelines prior to deployment.
Develop monitoring and observability systems to track model performance, data drift, data quality, and overall system health. Create and maintain end-to-end testing frameworks and simulation environments to validate models and pipelines prior to deployment. Work closely with Data Engineering and Platform Engineering teams to ensure ML systems integrate cleanly with broader Gridware infrastructure and operational standards.
What you’ll bring
All qualificationsCore experience
- 5+ years of experience building production ML infrastructure
- Experience with cloud platforms (AWS) and container orchestration (Kubernetes)
- Familiarity with feature stores, model registries, or centralized metadata systems (i.e.
Qualification wording
5+ years of experience building production ML infrastructure
Experience with cloud platforms (AWS) and container orchestration (Kubernetes)
Familiarity with feature stores, model registries, or centralized metadata systems (i.e. MLFlow)
Tools in this posting
- AWS
- Python
- Kubernetes
- MLflow
Source — Tool mentions in context
- Strong software engineering skills and proficiency in Python - Experience with cloud platforms (AWS) and container orchestration (Kubernetes) - Familiarity with feature stores, model registries, or centralized metadata systems (i.e. MLFlow)
- 5+ years of experience building production ML infrastructure - Strong software engineering skills and proficiency in Python - Experience with cloud platforms (AWS) and container orchestration (Kubernetes)
- Experience with cloud platforms (AWS) and container orchestration (Kubernetes) - Familiarity with feature stores, model registries, or centralized metadata systems (i.e. MLFlow) Senior ML Engineer Base Salary- $190,000-$210,000
Benefits in the posting
Full benefits wording- Health, Dental & Vision (Gold and Platinum with some providers plans fully covered)
- Paid parental leave
- Commuter allowance
- Company-paid training
- Employment type
- Full-Time
From the employer’s posting.
About Gridware
Gridware is a San Francisco-based technology company dedicated to protecting and enhancing the electrical grid.
In the employer’s words · Read in context
Job description
About Gridware
Gridware is a San Francisco-based technology company dedicated to protecting and enhancing the electrical grid. We pioneered a groundbreaking new class of grid management called active grid response (AGR), focused on monitoring the electrical, physical, and environmental aspects of the grid that affect reliability and safety. Gridware’s advanced Active Grid Response platform uses high-precision sensors to detect potential issues early, enabling proactive maintenance and fault mitigation. This comprehensive approach helps improve safety, reduce outages, and ensure the grid operates efficiently. The company is backed by climate-tech and Silicon Valley investors. For more information, please visit www.Gridware.io.
Role Description
As a Senior ML Infrastructure Engineer, you will work directly in the Automation org with the core ML, Ops, and Analytics teams to help improve and build out the infrastructure around model deployment and monitoring. This role is essential to helping scale out the amount of time saving’s Gridware brings to customers.
Responsibilities
- Design, build, and maintain the infrastructure, tooling, and workflows that enable reliable, scalable deployment of ML models to production.
- Develop monitoring and observability systems to track model performance, data drift, data quality, and overall system health.
- Create and maintain end-to-end testing frameworks and simulation environments to validate models and pipelines prior to deployment.
- Work closely with Data Engineering and Platform Engineering teams to ensure ML systems integrate cleanly with broader Gridware infrastructure and operational standards.
- Improve CI/CD pipelines for ML workloads, ensuring reproducibility, safe rollout, and automated rollback strategies.
Required Skills
- 5+ years of experience building production ML infrastructure
- Strong software engineering skills and proficiency in Python
- Experience with cloud platforms (AWS) and container orchestration (Kubernetes)
- Familiarity with feature stores, model registries, or centralized metadata systems (i.e. MLFlow)
Senior ML Engineer Base Salary- $190,000-$210,000
Staff ML Engineer Base Salary- $245,000-$250,000.
Salary
190,000 – 250,000 USD per year
**At this time, Gridware is unable to provide visa sponsorship or immigration support for this role. We’re only able to consider candidates who are currently authorized to work in the country of employment without visa sponsorship now or in the future.**
This describes the ideal candidate; many of us have picked up this expertise along the way. Even if you meet only part of this list, we encourage you to apply!
Gridware Technologies Inc. is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable federal, state, or local law.
Benefits
Health, Dental & Vision (Gold and Platinum with some providers plans fully covered)
Paid parental leave
Alternating day off (every other Monday)
“Off the Grid”, a two week per year paid break for all employees.
Commuter allowance
Company-paid training
Employment type
Full-Time
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
Complete your application on jobs.lever.co. The employer’s form will show what is required.
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Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Familiarity with feature stores, model registries, or centralized metadata systems (i.e. MLFlow) Senior ML Engineer Base Salary- $190,000-$210,000 Staff ML Engineer Base Salary- $245,000-$250,000.
More source context
Senior ML Engineer Base Salary- $190,000-$210,000 Staff ML Engineer Base Salary- $245,000-$250,000. Salary
More relevant text appears in the full description.
- Location & working pattern
San Francisco, CA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
190,000 – 250,000 USD per year **At this time, Gridware is unable to provide visa sponsorship or immigration support for this role. We’re only able to consider candidates who are currently authorized to work in the country of employment without visa sponsorship now or in the future.** This describes the ideal candidate; many of us have picked up this expertise along the way. Even if you meet only part of this list, we encourage you to apply!
- Status in our records
- Active
- First seen by us
- Apr 15, 2026
- Recorded sightings
- 142
- Last seen by us
- Oct 9, 2026
- Employer says posted
- Dec 11, 2025
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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