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Grid Engineer Jobs in Seattle, WA (NOW HIRING)

Grid

Machine Learning Engineer

Seattle, WA · On-site

$120K - $140K/yr

The Grid app lets users access cash, build credit, spend money, optimize their taxes, and lots ... You'll work closely with product, engineering and business leaders to make a difference with data.

Grid

Machine Learning Engineer

Seattle, WA

$120K - $140K/yr

The Grid app lets users access cash, build credit, spend money, optimize their taxes, and lots ... You'll work closely with product, engineering and business leaders to make a difference with data.

Grid

Senior Machine Learning Engineer

Seattle, WA

$150K - $220K/yr

The Grid app lets users access cash, build credit, spend money, optimize their taxes, and lots ... You'll work closely with product, engineering and business leaders to make a difference with data.

Grid

Senior Machine Learning Engineer

Seattle, WA · On-site

$150K - $220K/yr

The Grid app lets users access cash, build credit, spend money, optimize their taxes, and lots ... You'll work closely with product, engineering and business leaders to make a difference with data.

Logic20/20 Inc.

Manager - Grid Operations

Seattle, WA · On-site

We are seeking a Manager to join our Grid Operations practice with a strong engineering and consulting experience helping utilities modernize grid operations. This role is ideal for an experienced ...

Logic20/20 Inc.

Manager - Grid Operations

Seattle, WA · On-site

$138K - $185K/yr

We are seeking a Manager to join our Grid Operations practice with a strong engineering and consulting experience helping utilities modernize grid operations. This role is ideal for an experienced ...

Logic20/20 Inc.

Manager - Grid Operations

Seattle, WA · On-site

$138K - $185K/yr

We are seeking a Manager to join our Grid Operations practice with a strong engineering and consulting experience helping utilities modernize grid operations. This role is ideal for an experienced ...

Grid

Product Manager (Seattle on-site only)

Seattle, WA · On-site

$125K - $175K/yr

As a product manager at Grid, you'll build towards bold milestones in well-engineered, incremental releases. * Data Analysis: As a data-driven product and culture, we have robust data pipelines and ...

Grid

Product Manager (Seattle on-site only)

Seattle, WA · On-site

$120K - $175K/yr

As a product manager at Grid, you'll build towards bold milestones in well-engineered, incremental releases. * Data Analysis: As a data-driven product and culture, we have robust data pipelines and ...

Grid

Applied Scientist

Seattle, WA · On-site

$120K - $140K/yr

... engineering and business leaders to make a difference with data. With access to multiple robust datasets and clear research objectives, you'll have a significant impact on Grid's progress as a ...

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All JobsGrid Engineer JobsGrid Engineer Jobs in Seattle, WA

Grid Engineer information

See Seattle, WA salary details

$44.4K

$115.8K

$156.5K

How much do grid engineer jobs pay per year?

As of Sep 13, 2026, the average yearly pay for grid engineer in Seattle, WA is $115,795.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,600.00 and $132,600.00 per year, depending on experience, location, and employer.

What is a grid engineer?

A Grid Engineer is a professional who designs, operates, and maintains electrical grid systems that deliver electricity from power plants to consumers. They ensure the grid runs efficiently, safely, and reliably by overseeing infrastructure such as substations, transmission lines, and distribution networks. Grid Engineers play a crucial role in integrating renewable energy sources, managing grid stability, and addressing outages or emergencies. Their work often involves using advanced technology and data analysis to optimize grid performance.

What skills and qualifications are needed to thrive as a grid engineer?

To thrive as a Grid Engineer, you need a solid understanding of electrical engineering principles, power systems, and grid operations, typically backed by a bachelor's degree in electrical engineering or a related field. Familiarity with grid modeling software (such as PSS/E or PowerWorld), SCADA systems, and relevant certifications like Professional Engineer (PE) licensure are commonly required. Strong problem-solving, analytical thinking, and communication skills help Grid Engineers manage complex projects and collaborate with cross-functional teams. These competencies are essential to ensure safe, efficient, and reliable operation and modernization of electrical grids.

How does a grid engineer typically collaborate with other departments to ensure reliable power distribution?

Grid Engineers work closely with operations, maintenance, and planning teams to monitor grid performance and quickly address any faults or outages. They often coordinate with IT specialists to implement and maintain grid automation systems, and may also interact with regulatory and compliance departments to ensure all standards are met. Effective communication and teamwork are crucial, as Grid Engineers must translate technical data into actionable steps for various stakeholders, ensuring safe and efficient power delivery.

What is the difference between Grid Engineer vs Substation Engineer?

AspectGrid EngineerSubstation Engineer
CredentialsBachelor's in Electrical Engineering, relevant certificationsBachelor's in Electrical Engineering, relevant certifications
Work EnvironmentPower grid infrastructure, field and officeSubstation facilities, field and office
Industry UsagePower transmission and distribution companiesUtility companies, power plants
Primary FocusDesign, maintenance, and optimization of power gridsDesign, construction, and maintenance of substations

While both roles involve electrical engineering within the power industry, Grid Engineers focus on the overall power transmission network, ensuring efficient and reliable grid operation. Substation Engineers specialize in the design and maintenance of substations, which are critical nodes within the grid. Both roles require similar credentials and often work together to ensure a stable power supply.

What are popular job titles related to Grid Engineer jobs in Seattle, WA?

For Grid Engineer jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Grid Engineer jobs in Seattle, WA look for?

The top searched job categories for Grid Engineer jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Grid Engineer jobs?

Cities near Seattle, WA with the most Grid Engineer job openings:

Grid Engineer jobs near you
Infographic showing various Grid Engineer job openings in Seattle, WA as of September 2026, with employment types broken down into 1% Internship, 85% Full Time, 10% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $115,795 per year, or $55.7 per hour.

Machine Learning Engineer

Seattle, WA • On-site

Grid
See more jobs at Gridexternal

$120K - $140K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 17 days ago

Job description

About us
Today’s financial system is built to favor those with money. Grid’s mission is to level that playing field by building financial products that help users better manage their financial future. The Grid app lets users access cash, build credit, spend money, optimize their taxes, and lots, lots more.
 
Grid is a fast-growing team that’s deeply passionate about making a difference in the lives of millions. We’re solving huge problems and believe that every team member has a big role to play. Come join our growing team in our brand new Seattle office!
 
The role
We’re adding an Machine Learning Engineer to our team to help us build and scale our core product lines. You'll work closely with product, engineering and business leaders to make a difference with data. With access to multiple robust datasets and clear research objectives, you'll have a significant impact on Grid's progress as a business—as well as our users' happiness and success.
 
Projects will include fraud detection, prevention and mitigation in novel arenas, such as risk underwriting for various lending/advance programs; predictive analytics to drive our payout and repayments systems; and more.
 
The team
We're focused on serving our users and building a robust product and business above all else. To this end, Grid's team members experience high levels autonomy and ownership, and as a company we value curiosity, learning and growth.
 
As an Machine Learning Engineer, you'll have an opportunity not only to identify key leverage points for our data products, but also to set the standard for Grid's statistical inference and machine learning practice.
 
The tech stack
Our backend tech stack is based on Python, GCP, Go, protobufs, BigQuery and MySQL. We have built our platform from the ground up to optimize for clean data sources, and we have made numerous investments into data warehousing, streaming analytics infrastructure and offline data cleanliness. As a result, we think Grid is positioned for efficient and powerful applied science.
What you'll do
  • Research & Analysis: Perform data research and analysis using Grid's proprietary dataset as well as other relevant sources
  • Model Development: Develop and validate models that enable strategically relevant business objectives, such as enabling growth, mitigating fraud, controlling risk, etc.
  • Deployment & Iteration: Iterate on new and existing models based on feedback from team and real-world performance
  • Productionization: Collaborate with data engineers, product managers to help translate your work into production-grade, high scaled data products
  • Present Findings: Present your findings and communicate with members of the team with varying levels of technical depth
  • Foster DS @ Grid: Help build out our Applied Science and Machine Learning as a team and practice at Grid
What we're looking for:
  • Applied Science Expertise: Proven experience in Machine Learning and/or Applied Science, including a strong background in statistical inference, machine learning. This is a requirement, a bachelors or master's degree in Statistics, Mathematics, Physics, or Computer Science with a focus on machine learning is required. We are currently not accepting applicants with bachelor or master's degrees in Business Analytics, Information Systems, or Data Science.
  • Deep Expertise in Applied Science & Machine Learning: Proven experience in applied machine learning, including a deep understanding of statistical inference and predictive modeling. Demonstrated practical experience with deep learning techniques, particularly transformer-based models.
  • Research to Implementation Proficiency: A strong track record of reading, understanding, and implementing research papers in machine learning or related fields.
  • Robust Technical Skills: Hands-on experience with Python (with libraries like PyTorch/TensorFlow) and SQL is essential.
  • Autonomy and Initiative: Ability to work independently and take ownership of projects, showcasing a proactive approach to identifying key leverage points for data products.
  • Curiosity and Optimism: People who are constantly asking why the world around them works the way it does, and who have the will to change it.
  • Technical Skills: Proficiency in the modern machine learning techniques, such as Model Evaluation and Validation, Deep Learning and Time Series Analysis, Logistic Regression, Naive Bayes, Tree based Models (i.e., Random Forest).
  • Self Starter: Confidence to prioritize work and delivery demonstrable results on a tight cadence.
  • Domain Knowledge: Demonstrated experience or understanding of the financial industry, especially in the context of building and scaling FinTech products.
Benefits
Medical
Dental
Vision
401K
Life Insurance
 
Salary Range
$120,000 - $140,000 per year

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.