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Principal Machine Learning Engineer Jobs in Seattle, WA

We are seeking a Principal Machine Learning Engineer to accelerate our training of generative models in close collaboration with Maching Learning (ML) researchers, software engineers, and domain ...

As a Principal ML Engineer at Dedrone, you will contribute to architecting and implementing the ... new machine learning models and AI capabilities, leading to better and more responsible AI ...

As a Principal ML Engineer at Dedrone, you will contribute to architecting and implementing the ... new machine learning models and AI capabilities, leading to better and more responsible AI ...

As a Machine Learning Engineer on the Generative AI Services team, you will lead the architecture, design and development of distributed, scalable, and high-performance systems for AI model training ...

The Principal AI Agent / ML Software Engineer is a Senior Staff-level, hands-on technical leadership role responsible for defining, building, and operating next-generation AI systems on Oracle Cloud ...

The Principal AI Agent / ML Software Engineer is a Senior Staff-level, hands-on technical leadership role responsible for defining, building, and operating next-generation AI systems on Oracle Cloud ...

Partner with executive leadership, engineering, product, and data science teams to ensure AI ... Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) * Experience ...

Partner with executive leadership, engineering, product, and data science teams to ensure AI ... Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) * Experience ...

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Principal Machine Learning Engineer information

See Seattle, WA salary details

$84.3K

$167.6K

$242K

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

As of Jul 20, 2026, the average yearly pay for principal machine learning engineer in Seattle, WA is $167,635.00, according to ZipRecruiter salary data. Most workers in this role earn between $134,900.00 and $197,000.00 per year, depending on experience, location, and employer.

What types of projects and responsibilities can a Principal Machine Learning Engineer typically expect in this role?

Principal Machine Learning Engineers are often tasked with leading the design, development, and deployment of large-scale machine learning models and systems that address key business challenges. In this role, you will collaborate closely with data scientists, engineers, and product managers to define project requirements, architect solutions, and ensure high-quality delivery. You may also guide research initiatives, oversee code and model reviews, and mentor junior engineers, helping to shape the technical direction of the team. Typical responsibilities can range from prototyping and optimizing algorithms to ensuring models are scalable, reliable, and aligned with organizational goals.

What are the key skills and qualifications needed to thrive in the Principal Machine Learning Engineer position, and why are they important?

To thrive as a Principal Machine Learning Engineer, you need advanced expertise in machine learning algorithms, statistical analysis, software engineering, and a strong background in computer science or related fields, often supported by a master's or PhD degree. Familiarity with tools such as Python, TensorFlow, PyTorch, cloud platforms (AWS, GCP, Azure), and relevant certifications strengthens technical capability. Leadership, strategic thinking, effective communication, and mentorship are vital soft skills for guiding teams and collaborating across departments. These competencies are essential for driving innovation, ensuring technical excellence, and influencing organizational AI initiatives.

Will MLE be replaced by AI?

Principal Machine Learning Engineers design, develop, and oversee AI and machine learning systems, and their roles involve understanding complex algorithms, data management, and model deployment. While AI automates certain tasks, MLE roles focus on building and maintaining AI infrastructure, which requires human expertise, critical thinking, and ongoing innovation that AI cannot fully replace. The role is expected to evolve alongside advancements in AI technology but remains essential for guiding AI development and ensuring ethical, effective implementation.

What does a Principal Machine Learning Engineer do?

A Principal Machine Learning Engineer leads the design, development, and deployment of machine learning models and systems. They set technical strategy, mentor engineers, and collaborate with cross-functional teams to solve complex AI challenges. Their role often includes researching new algorithms, optimizing model performance, and ensuring scalability in production environments. Additionally, they work closely with data scientists, software engineers, and product managers to align ML initiatives with business objectives.

How much do principal AI engineers make?

Principal AI engineers typically earn between $130,000 and $200,000 annually, with salaries varying based on experience, location, and industry. They often have advanced skills in machine learning, deep learning, and data science, and may receive bonuses or stock options as part of compensation packages.

What engineers make $300,000 a year?

Principal Machine Learning Engineers and senior data scientists in the tech industry often earn $300,000 or more annually, especially with extensive experience, advanced skills in deep learning and AI, and working at large technology companies or startups with competitive compensation packages. High salaries may also include bonuses, stock options, and other benefits.

What engineer makes $500,000 a year?

A Principal Machine Learning Engineer can earn $500,000 or more annually, especially with extensive experience, advanced skills in deep learning and data science, and working at large tech companies or in high-demand industries. Compensation often includes base salary, bonuses, and stock options, reflecting their seniority and expertise.
What job categories do people searching Principal Machine Learning Engineer jobs in Seattle, WA look for? The top searched job categories for Principal Machine Learning Engineer jobs in Seattle, WA are:
Infographic showing various Principal Machine Learning Engineer job openings in Seattle, WA as of July 2026, with employment types broken down into 89% Full Time, 7% Part Time, 1% Temporary, and 3% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution, with an average salary of $167,635 per year, or $80.6 per hour.
Principal Machine Learning Engineer

Principal Machine Learning Engineer

Microsoft

Redmond, WA • On-site

$188K - $304K/yr

Full-time

Posted 21 days ago


Microsoft rating

8.5

Company rating: 8.5 out of 10

Based on 131 frontline employees who took The Breakroom Quiz

68th of 209 rated software companies


Job description

Overview
Health Futures is a Research and Incubation team working at the intersection of computer science, signal processing, machine learning, and biomedicine. We are a global and diverse team of engineers, scientists, and medical doctors who are working on next-generation Artificial Intelligence (AI) tools and methods for health and life sciences. We offer a unique and vibrant environment that features innovative academic research, enterprise software development, and real-world delivery, with close feedback loops and rapid iterations among all three, much like a lean startup. Our mission is to empower every person on the planet to live a healthier future.
We are seeking a Principal Machine Learning Engineer to accelerate our training of generative models in close collaboration with Maching Learning (ML) researchers, software engineers, and domain experts. This is a hands-on technical role focused on advancing state-of-the-art model capabilities across a variety of scientific domains and modalities. You'll spend your time working across the stack from curriculum design, to debugging training runs, through developing new evaluation methods and high-performance inferencing - with a goal of improving all phases of our training process.
As part of Health Futures, you'll have the opportunity to tackle everything from model training to data and evaluation pipelines. Your work will span the full spectrum of model development - training and optimizing models on the latest hardware, devising new ways to assess their capabilities, and evolving data and training workflows to maximize model utility. Beyond model training, you'll participate in explorations of how these models can and should be used in the real world - and the systems required to successfully operate them.
At Microsoft, our mission-to empower every person and every organization on the planet to achieve more-guides how we partner with customers to deliver trusted, impactful solutions. With a growth mindset culture, we innovate responsibly and measure success by shared progress-people, teams, and customers. Join us to do meaningful work that changes the world and helps shape what's next for everyone.
Responsibilities
  • Lead the design and development of machine learning models and systems for health and life sciences applications, ensuring scalability and reliability.
  • Define technical strategy and architecture for ML pipelines, including data ingestion, feature engineering, model training, evaluation, and deployment.
  • Collaborate with interdisciplinary teams (including scientists, researchers, and software engineers) to envision and develop AI-augmented scientific systems.
  • Mentor engineers and researchers, promoting best practices in ML development, experimentation, and responsible AI principles.
  • Ensure security, privacy, and regulatory compliance across ML workflows and data handling.

Qualifications
Required Qualifications
  • Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C++, C#, Java, JavaScript, or Python
    • OR equivalent experience.

Preferred Qualifications
  • Masters in Computer Science or related technical field AND 6+ years technical engineering experience including significant work in machine learning or applied AI
    • OR equivalent experience.
  • Proven track record of designing and deploying large-scale ML or MLops systems in research or product settings.
  • Hands-on experience with large-scale distributed training of ML models.
  • Deep expertise in ML algorithms, model optimization, and frameworks (e.g., PyTorch, TensorFlow).
  • Experience with one or more of: optimizing data mixes, mid-training, post-training, model merging, or model distillation.
  • Familiarity with security and compliance standards for enterprise and health data.
  • Demonstrated ability to communicate effectively and solve problems in collaborative, research-driven environment.

#Research #healthfutures #researchsystems
Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 - $304,200 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

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About Microsoft

Sourced by ZipRecruiter

Our infrastructure is comprised of a large global portfolio of more than 100 datacenters and 1 million servers. Our foundation is built upon and managed by a team of subject matter experts working to support services for more than 1 billion customers and 20 million businesses in over 90 countries worldwide. With environmental sustainability and optimization at the forefront of our datacenter design and operations, we continue to grow and evolve as we meet the ever-changing business demands that hold Microsoft as a world-class cloud provider.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

Redmond, WA, US

Year founded

1975

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