Senior ML Engineer Jobs in Washington
Senior ML Engineer jobs in Washington are among the most active in the country, concentrated in cloud infrastructure, autonomous systems, and enterprise AI across a market that supports roles from mid-level to principal. Seattle anchors the majority of hiring, with Bellevue and Redmond close behind, and employers like Amazon, Microsoft, and Boeing maintaining deep, sustained demand for machine learning talent in Washington. The most sought-after specialties are large language model fine-tuning, MLOps and model deployment pipelines, and computer vision applied to robotics or remote sensing. Find a role that fits below and apply directly.
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Showing 5 of 162+ Senior ML Engineer jobs
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Kirkland, WA, USA; Seattle, WA, USA; Sunnyvale, CA, USA.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development (e.g., Python).
- 7 years of experience leading technical project strategy, ML design, and working with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 5 years of experience with one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- 5 years of experience with design and architecture; and testing/launching software products.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 5 years of experience in a technical leadership role leading project teams and setting technical direction.
- Experience with ML modeling and scaling.
- Experience with large-scale distributed systems or machine learning systems (Training for LLM, image generation).
- Experience with building cloud based services, including with GCP.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
Google’s revolutionary Cloud TPUs were designed from the ground up to accelerate machine learning workloads, providing the computational power to train and run machine learning models in a fraction of the time and cost conventionally required. With the new Google Cloud Platform (GCP) Cloud TPU service and Google Kubernetes Engine (GKE) support, it's easy to take your existing ML workloads on leading ML frameworks (PyTorch and JAX) and move them to the cloud to take advantage of this great capability.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Build and deliver ML frameworks to perform training at Large Language Model (LLMS) and stable diffusion models for Google Cloud customers.
- Design and implement AI frameworks software for ML workloads in the cloud that enables models for language modeling, stable diffusion, rankings and recommendations, etc.
- Identify and resolve issues in software, performance, and topology.
- Work closely with software engineers, product managers and other engineering teams to get high-quality products and features through the software project lifecycle.
- Design, develop, test, deploy, maintain, and improve software.
In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Kirkland, WA, USA; Seattle, WA, USA; Sunnyvale, CA, USA.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development (e.g., Python).
- 7 years of experience leading technical project strategy, ML design, and working with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 5 years of experience with one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- 5 years of experience with design and architecture; and testing/launching software products.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 5 years of experience in a technical leadership role leading project teams and setting technical direction.
- Experience with ML modeling and scaling.
- Experience with large-scale distributed systems or machine learning systems (Training for LLM, image generation).
- Experience with building cloud based services, including with GCP.
About the job
Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
Google’s revolutionary Cloud TPUs were designed from the ground up to accelerate machine learning workloads, providing the computational power to train and run machine learning models in a fraction of the time and cost conventionally required. With the new Google Cloud Platform (GCP) Cloud TPU service and Google Kubernetes Engine (GKE) support, it's easy to take your existing ML workloads on leading ML frameworks (PyTorch and JAX) and move them to the cloud to take advantage of this great capability.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $262000 - $364000 (USD) + 25% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Build and deliver ML frameworks to perform training at Large Language Model (LLMS) and stable diffusion models for Google Cloud customers.
- Design and implement AI frameworks software for ML workloads in the cloud that enables models for language modeling, stable diffusion, rankings and recommendations, etc.
- Identify and resolve issues in software, performance, and topology.
- Work closely with software engineers, product managers and other engineering teams to get high-quality products and features through the software project lifecycle.
- Design, develop, test, deploy, maintain, and improve software.
See All 162+ Senior ML Engineer Jobs in Washington
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Find Senior ML Engineer JobsSenior ML Engineer Jobs by City in Washington
Where Washington roles are concentrated, by current openings.
Senior ML Engineer Job Market in Washington
A snapshot from current Washington openings, updated as new roles post.
Who's Hiring
- TikTok48
- Meta12
- ByteDance10
- Amazon10
- Amazon Web Services6
Top Industries Hiring
- Technology & Software25
- Electronics & Hardware5
- Insurance3
- Retail2
- Social Media2
What Washington Employers Look For
The qualifications that appear most often in senior ML engineer jobs across Washington.
- Bachelor's or master's degree in computer science, statistics, or a closely related field
- Five or more years of hands-on experience designing and deploying machine learning models in production
- Proficiency in Python and familiarity with frameworks such as PyTorch or TensorFlow
- Experience building and maintaining ML pipelines on cloud platforms, particularly AWS or Azure
- Strong background in data engineering, feature engineering, and model evaluation methodology
- Demonstrated ability to lead cross-functional projects and mentor junior ML engineers
Senior ML Engineer Jobs in Washington: Frequently Asked Questions
How do you become a senior ml engineer in Washington?
Senior ml engineer roles in Washington do not require a state-issued license or registration. The typical path is a bachelor's or master's degree in computer science, statistics, or machine learning, followed by several years of progressive industry experience building and shipping ML systems. Washington employers, particularly those in the Seattle-Bellevue corridor, strongly favor candidates with demonstrated production experience, a portfolio of shipped models, and familiarity with cloud-native ML infrastructure.
How much do senior ML engineers make in Washington?
Senior ML engineers in Washington earn a median of about $128,940 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $60,210 for the lowest 10% to over $200,610 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire senior ml engineers in Washington?
Employers hiring senior ml engineers in Washington right now include TikTok, Meta, and ByteDance, based on current listings on Migrate Mate as of November 2026. Washington's concentration of major cloud and aerospace companies means demand is sustained year-round, with teams across Seattle, Bellevue, and Redmond actively competing for machine learning talent.
Which Washington cities have the most senior ml engineer jobs?
Seattle, Bellevue, and Redmond have the most senior ml engineer openings in Washington. Seattle leads because it is home to major technology and cloud company headquarters, while Bellevue and Redmond draw significant hiring from Microsoft's main campus and the dense cluster of enterprise software and AI startups that have grown around it.
Are there remote senior ml engineer jobs in Washington?
Yes, and more than most fields. About 30% of senior ml engineer openings tied to Washington are remote or hybrid as of November 2026, reflecting how well the role translates to distributed work. Research, model training, and pipeline development are the parts of the job most commonly done fully remote, while roles requiring close collaboration with hardware or robotics teams tend to remain on-site.
How can I get hired as a senior ml engineer in Washington with little or no experience?
The most realistic entry path is a machine learning internship or new-grad program at one of Washington's major technology employers, where structured rotations provide production exposure quickly. Amazon, Microsoft, and a range of Bellevue-based AI startups regularly run university hiring pipelines for roles like ML engineer I or applied scientist. Building a public project portfolio on GitHub, contributing to open-source ML tooling, and earning cloud certifications from AWS or Azure gives candidates without industry experience a credible foothold in Washington's competitive market.
Where can I find and apply to senior ml engineer jobs in Washington?
You can find and apply to senior ml engineer jobs in Washington on Migrate Mate, which lists current Washington openings. Search the available roles, find the ones that fit your background and location, and apply directly to each one.
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Find roles in Washington that match your experience and apply in just a few clicks.
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