Sr Staff Machine Learning Engineer Jobs in Washington
Sr Staff Machine Learning Engineer jobs in Washington represent one of the most active and competitive markets in the country, concentrated in cloud infrastructure, autonomous systems, and enterprise AI across companies at every seniority level from mid-career engineer through principal and distinguished. Most hiring is anchored in Seattle and its eastside corridor, including Bellevue and Redmond, where Microsoft, Amazon, and Google maintain large ML research and applied engineering organizations. The most in-demand specialties are large language model development, recommendation and ranking systems, and MLOps infrastructure. Find a role that fits below and apply directly.
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Showing 5 of 18+ Sr Staff Machine Learning 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 18 Sr Staff Machine Learning Engineer Jobs in Washington
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Find JobsSr Staff Machine Learning Engineer Jobs by City in Washington
Where Washington roles are concentrated, by current openings.
Sr Staff Machine Learning Engineer Job Market in Washington
A snapshot from current Washington openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
- Insurance
- Retail
- Automotive
- Artificial Intelligence
What Washington Employers Look For
The qualifications that appear most often in sr staff machine learning engineer jobs across Washington.
- PhD or MS in machine learning, computer science, or a related quantitative field required
- Ten or more years of applied machine learning engineering experience at scale
- Expertise in training and deploying large models on distributed cloud infrastructure
- Demonstrated technical leadership, including mentoring staff and principal-level engineers
- Proficiency in Python plus deep learning frameworks such as PyTorch or TensorFlow
- Experience with MLOps platforms and production model monitoring in high-traffic systems
Sr Staff Machine Learning Engineer Jobs in Washington: Frequently Asked Questions
How do you become a sr staff machine learning engineer in Washington?
There is no state-issued license required to work as a sr staff machine learning engineer in Washington. The typical path begins with a bachelor's degree in computer science, mathematics, or a related field, followed by graduate study at the MS or PhD level. Washington's major tech employers consistently prefer candidates who have advanced from software engineering or research scientist roles, built production ML systems at scale, and demonstrated the technical scope and cross-team influence expected at the staff and senior staff levels.
How much do sr staff machine learning engineers make in Washington?
Sr staff machine learning engineers in Washington earn a median of about $166,540 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $96,810 for the lowest 10% to over $255,350 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire sr staff machine learning engineers in Washington?
Employers hiring sr staff machine learning engineers in Washington right now include GEICO, Uber, and Rippling, based on current listings on Migrate Mate as of November 2026. Washington's density of cloud, retail technology, and autonomous-systems companies makes it one of the few states where sr staff-level ML roles appear consistently across multiple large employers simultaneously.
Which Washington cities have the most sr staff machine learning engineer jobs?
Seattle and Kirkland have the most sr staff machine learning engineer openings in Washington. Seattle drives the largest share because Amazon and Google maintain major ML research and engineering organizations there, while Bellevue and Redmond draw heavily from Microsoft's AI and cloud divisions, making the greater Puget Sound corridor the undisputed center of sr staff ML hiring in the state.
Are there remote sr staff machine learning engineer jobs in Washington?
Yes, and more than most fields. About 40% of sr staff machine learning engineer openings tied to Washington are remote or hybrid as of November 2026, reflecting how much of this work centers on code, cloud infrastructure, and asynchronous collaboration rather than physical presence. Roles focused on research, model development, and MLOps tooling are most likely to offer fully remote or flexible arrangements.
How can I get hired as a sr staff machine learning engineer in Washington with little or no experience?
The most realistic entry path is through a machine learning engineer or research scientist role at a Washington company, building toward staff-level scope over time. Amazon, Microsoft, and Google each run structured university hiring programs and internship pipelines in the Seattle area that place new graduates into junior ML roles. Completing a recognized graduate program, publishing research, or contributing to open-source ML projects gives candidates a concrete edge when applying to these programs, with promotion to senior and staff levels coming through demonstrated production impact.
Where can I find and apply to sr staff machine learning engineer jobs in Washington?
You can find and apply to sr staff machine learning engineer jobs in Washington on Migrate Mate, which lists current Washington openings. Find roles that fit your background and apply directly to the ones that match.
See All 18 Sr Staff Machine Learning Engineer Jobs in Washington
Find roles in Washington that match your experience and apply in just a few clicks.
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