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Machine Learning Engineer Jobs in Sammamish, WA (NOW HIRING)

Adobe

Principal Machine Learning Engineer

Seattle, WA · On-site

We are hiring a Principal Machine Learning Engineer to serve as the technical lead for our GenAI Services area. This is not a model-training or research role - it is the senior-most hands-on ...

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 ...

Apple

AIML - Machine Learning Engineer, MIND

Seattle, WA

$142K - $263K/yr

As a Machine Learning Engineer in the Machine Intelligence Neural Design (MIND) team, you will have an opportunity to be part of an ML innovation organization within Apple that has its roots in the ...

Expedia

Machine Learning Engineer III

Seattle, WA · On-site

$252K/yr

We are seeking a Machine Learning Engineer II to join our Advertising Technology team, where we build and operate large-scale batch and real-time ML systems that power pricing, inventory optimization ...

New

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 ...

Chewy

Machine Learning Engineer III

Bellevue, WA · On-site

$148K - $225K/yr

The Chewy Sponsored Ads team is looking for a Senior Machine Learning Engineer in Bellevue, WA to help launch various innovative ads offerings for our sponsored advertisement initiatives. As ...

Chewy

Machine Learning Engineer III

Bellevue, WA · On-site +1

$148K - $225K/yr

The Chewy Sponsored Ads team is looking for a Senior Machine Learning Engineer in Bellevue, WA to help launch various innovative ads offerings for our sponsored advertisement initiatives. As ...

DocuSign

Senior Machine Learning Engineer

Seattle, WA · On-site +1

$186K - $300K/yr

What you'll do We are looking for a Senior Machine Learning Engineer to redefine how we operate our global services. You won't just be building dashboards; you will be building the "brain" of our ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Sammamish, WA

Machine Learning Engineer information

See Sammamish, WA salary details

$35.2K

$144K

$216.3K

How much do machine learning engineer jobs pay per year?

As of Sep 1, 2026, the average yearly pay for machine learning engineer in Sammamish, WA is $143,954.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,500.00 and $173,300.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

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

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs

What job categories do people searching Machine Learning Engineer jobs in Sammamish, WA look for?

The top searched job categories for Machine Learning Engineer jobs in Sammamish, WA are:

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

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

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Sammamish, WA as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $143,954 per year, or $69.2 per hour.

Principal Machine Learning Engineer

Extreme Networks

Seattle, WA

Full-time

Re-posted 6 days ago

Job description

Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions. They rely on our top-rated services and support to accelerate their digital transformation efforts and deliver unprecedented progress. With double-digit growth year over year, no provider is better positioned to deliver scalable outcomes than Extreme.

Inclusion is one of our core values and in our DNA. We are committed to fostering an inclusive workplace that embraces our differences and creates an atmosphere where all our employees thrive because of their differences, not in spite of them.

Become part of Something big with Extreme! As a global networking leader, learn why there's no better time to join the Extreme team.

Principal Machine Learning Engineer
Experience: 12 to 18 years
Skills: Python/Java, Cloud, PyTorch, CUDA, MapReduce, Spark, Flink, Kafka, PySpark, SageMaker
 
About the position
 
Are you energized by the idea of innovating with generative AI? Do you aspire to create a global impact while tackling challenges at the forefront of machine learning? Do you want to be part of the team working on ground-breaking products that define the future of AI-driven network management?  Then come, advance with us. This is an incredible opportunity to innovate new networking experiences while working at the cutting edge of IOT, big data, cloud computing, ML and generative AI. This is a greenfield project in which you will help define every aspect of user and product experience and drive significant portions of the technical and scientific roadmaps.
There has never been a better time to join Extreme, after several acquisitions extending our portfolio and go-to market strategy, we have seen enormous opportunity and growth within the regions. Aside from being a Technology Leader in the Gartner Magic Quadrant, we also adamantly promote an internal culture that truly embraces diversity, inclusion, and equality in the workplace. Having Diversity and Inclusion as part of our core values and beliefs, we're proud to foster an environment where every Extreme employee can thrive because of their differences, not despite them. Our moto here at Extreme is 'Advance with us' and it applies to everyone we work with - inside and outside the company.
Our group is responsible for developing core solutions in data mining, machine learning, anomaly detection and natural language processing, positively impacting multiple existing Extreme flagship products and new offerings from the company. We are spearheading a fundamental shift in how businesses think about managing their wired and wireless networks by building high-performance, real-time multi-agent systems that can perceive, learn, and act intelligently on behalf of humans.  As a part of this group, you will constantly experiment with new technologies, innovate best-in class networking experiences, and launch state of the art machine learning and data mining solutions.
Responsibilities
  • Be a thought leader and forward thinker, help drive an innovative vision for our various products and platforms, design and launch strategic machine learning (ML) solutions and drive business-wide innovation.
  • Take the lead in the end-to-end software development lifecycle, encompassing design, testing, deployment, and operations, lead technical discussions and strategy, and participate hands-on in design reviews, code reviews, and implementation.
  • Craft high-performance, production-ready machine learning code for our next-generation real-time ML platform. Extend existing ML libraries and frameworks.
  • Working closely with other engineers and scientists, lead solutions to accelerate model development, validation and experimentation cycles, and integrate models and algorithms in production systems at a very large scale.
  • Mentor and develop other engineers on the team, establish technical direction and foster team culture.
  • Uphold the highest standards of technical rigor in engineering and operational excellence, build highly resilient and scalable systems, and champion operational and process improvements.
Qualifications:
  • Degree in mathematics/computer science or related discipline.
  • 12+ years of experience in the complete software development lifecycle including design, coding, code reviews, testing, build processes, deployments and operations.
  • 7+ years of experience in programming, with proficiency in at least one programming language, preferably Python or Java.
  • 5+ years of experience in leading the design and architecture of large distributed systems preferably on cloud platforms (e.g., AWS, Azure, Google Cloud).
  • Experience working with distributed data and ML technologies (e.g. MapReduce, Spark, Flink, Kafka, PySpark, SageMaker etc.).
  • Experience as a mentor, tech lead or leading an engineering team.
  • Adept at tackling highly complex, ambiguous or undefined problems.
Preferred Qualifications:
  • MS or PhD in Computer Science or equivalent experience in ML.
  • Experience dealing with real world large-scale datasets.
  • Prior experience delivering end-to-end ML solutions, including data preparation, training, fine-tuning and deployment of large models.
  • Prior experience in developing ML optimization techniques in frameworks like PyTorch and CUDA.
 
Come work with a team of highly talented engineers, and advance with us to achieve new heights every day!
Extreme Networks, Inc. (EXTR) creates effortless networking experiences that enable all of us to advance. We push the boundaries of technology leveraging the powers of machine learning, artificial intelligence, analytics, and automation. Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions and rely on our top-rated services and support to accelerate their digital transformation efforts and deliver progress like never before. For more information, visit Extreme's website or follow us on Twitter, LinkedIn, and Facebook.

We encourage people from underrepresented groups to apply. Come Advance with us! In keeping with our values, no employee or applicant will face discrimination/harassment based on: race, color, ancestry, national origin, religion, age, gender, marital domestic partner status, sexual orientation, gender identity, disability status, or veteran status. Above and beyond discrimination/harassment based on "protected categories," Extreme Networks also strives to prevent other, subtler forms of inappropriate behavior (e.g., stereotyping) from ever gaining a foothold in our organization. Whether blatant or hidden, barriers to success have no place at Extreme Networks.
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.
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