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Senior Machine Learning Engineer Jobs in Kenmore, WA

Grid

Senior Machine Learning Engineer

Seattle, WA · 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 ...

Grid

Senior Machine Learning Engineer

Seattle, WA · 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 ...

Hive

Senior Machine Learning Engineer

Seattle, WA · On-site

$160K - $250K/yr

Senior Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at ...

Hive

Senior Machine Learning Engineer

Seattle, WA · On-site

$160K - $250K/yr

Senior Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at ...

Expedia

Senior Machine Learning Engineer

Seattle, WA · On-site

$139K - $183K/yr

This Senior Machine Learning Engineer role is part of the Distribution & Supply team which sits within our Technology division. The Distribution & Supply team builds and optimizes the machine ...

PitchBook Data

Sr. Machine Learning Engineer

Seattle, WA · On-site

$118K - $163K/yr

As a Senior Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role in delivering AI-powered features that extract meaningful insights from PitchBook's wealth of ...

Adobe

Senior Machine Learning Engineer

Seattle, WA · On-site

$172K - $306K/yr

What You'll Do As a Senior Machine Learning Engineer on the Content Intelligence team, you will lead the development of ML models and systems, to assist with Content Understanding. You will work ...

PitchBook Data

Sr. Machine Learning Engineer

Seattle, WA · On-site

$139K - $183K/yr

As a Senior Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role in delivering AI-powered features that extract meaningful insights from PitchBook's wealth of ...

FieldAI

Senior Machine Learning Engineer

Seattle, WA · On-site

$150 - $200/hr

You'll collaborate closely with machine learning scientists, software engineers, and robotics experts to design and implement FFM capabilities that generalize across tasks and environments. Beyond ...

Axon

Senior Machine Learning Engineer

Seattle, WA · On-site

$139K - $183K/yr

As a Machine Learning Engineer at Axon , you'll help build AI solutions that are transforming public safety and advancing our mission to Protect Life . You'll work alongside talented ML engineers and ...

Axon

Senior Machine Learning Engineer

Seattle, WA · On-site

$139K - $183K/yr

As a Machine Learning Engineer at Axon , you'll help build AI solutions that are transforming public safety and advancing our mission to Protect Life . You'll work alongside talented ML engineers and ...

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All JobsMachine Learning Engineer JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in Kenmore, WA

Senior Machine Learning Engineer information

See Kenmore, WA salary details

$65.9K

$140.1K

$203.1K

How much do senior machine learning engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for senior machine learning engineer in Kenmore, WA is $140,077.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,700.00 and $158,800.00 per year, depending on experience, location, and employer.

What does a senior machine learning engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What are the key skills and qualifications needed to thrive as a senior machine learning engineer, and why are they important?

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

What is the difference between Senior Machine Learning Engineer vs Data Scientist?

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Kenmore, WA?

The most popular types of Machine Learning Engineer jobs in Kenmore, WA are:

What are popular job titles related to Senior Machine Learning Engineer jobs in Kenmore, WA?

For Senior Machine Learning Engineer jobs in Kenmore, WA, the most frequently searched job titles are:

What cities near Kenmore, WA are hiring for Senior Machine Learning Engineer jobs?

Cities near Kenmore, WA with the most Senior Machine Learning Engineer job openings:

Senior Machine Learning Engineer jobs near you
Infographic showing various Senior Machine Learning Engineer job openings in Kenmore, WA as of September 2026, with employment types broken down into 95% Full Time, and 5% Contract. Highlights an 87% In-person, 2% Hybrid, and 11% Remote job distribution, with an average salary of $140,077 per year, or $67.3 per hour.

Senior Machine Learning Engineer

Seattle, WA • On-site

Grid
See more jobs at Gridexternal

$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.