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Entry Level Google Cloud Machine Learning Engineer Jobs in Seattle, WA

Senior Machine Learning Engineer

Seattle, WA ยท On-site

$150K - $220K/yr

The role We're adding Senior 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 ...

Senior Machine Learning Engineer

Seattle, WA ยท On-site

$150K - $220K/yr

The role We're adding Senior 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 ...

Run and scale training experiments on cloud or HPC (AWS, GCP, SLURM, Ray), and debug throughput, stability, and convergence issues * Build evaluation harnesses and benchmark infrastructure, with held ...

Run and scale training experiments on cloud or HPC (AWS, GCP, SLURM, Ray), and debug throughput, stability, and convergence issues * Build evaluation harnesses and benchmark infrastructure, with held ...

Run and scale training experiments on cloud or HPC (AWS, GCP, SLURM, Ray), and debug throughput, stability, and convergence issues * Build evaluation harnesses and benchmark infrastructure, with held ...

Run and scale training experiments on cloud or HPC (AWS, GCP, SLURM, Ray), and debug throughput, stability, and convergence issues * Build evaluation harnesses and benchmark infrastructure, with held ...

Run and scale training experiments on cloud or HPC (AWS, GCP, SLURM, Ray), and debug throughput, stability, and convergence issues * Build evaluation harnesses and benchmark infrastructure, with held ...

Run and scale training experiments on cloud or HPC (AWS, GCP, SLURM, Ray), and debug throughput, stability, and convergence issues * Build evaluation harnesses and benchmark infrastructure, with held ...

As a Machine Learning Engineer specializing in knowledge graphs, you will work closely with cross-functional teams to design, implement, and optimize algorithms and models that enable efficient ...

Machine Learning Engineer, New Grad

Bellevue, WA ยท On-site +1

$117K - $152K/yr

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply ...

Machine Learning Engineer

Seattle, WA ยท On-site

$150 - $200/hr

Partner with data engineering and product pods to put predictions in the tools people already use. What We're Looking For * The below is a starting point. We always make space for exceptional people ...

Showing results 21-40

Entry Level Google Cloud Machine Learning Engineer information

See Seattle, WA salary details

$34.1K

$78.9K

$134.3K

How much do entry level google cloud machine learning engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for entry level google cloud machine learning engineer in Seattle, WA is $78,936.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,600.00 and $89,300.00 per year, depending on experience, location, and employer.

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Infographic showing various Entry Level Google Cloud Machine Learning Engineer job openings in Seattle, WA as of June 2026, with employment types broken down into 45% Full Time, 29% Part Time, 24% Contract, and 2% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $78,936 per year, or $38 per hour.

Senior Machine Learning Engineer

Seattle, WA โ€ข On-site

$150K - $220K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 27 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 Senior 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 a Senior 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
$150,000 - $220,000 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.