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Scientific Machine Learning Jobs in Seattle, WA (NOW HIRING)

Senior Machine Learning Scientist

Seattle, WA · On-site

$104K - $142K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a ...

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Scientific Machine Learning information

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$15

$35

$59

How much do scientific machine learning jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for scientific machine learning in Seattle, WA is $35.82, according to ZipRecruiter salary data. Most workers in this role earn between $21.88 and $45.67 per hour, depending on experience, location, and employer.

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in scientific machine learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

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

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

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

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Seattle, WA? For Scientific Machine Learning jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Seattle, WA look for? The top searched job categories for Scientific Machine Learning jobs in Seattle, WA are:
What cities near Seattle, WA are hiring for Scientific Machine Learning jobs? Cities near Seattle, WA with the most Scientific Machine Learning job openings:

Applied Scientist - Machine Learning, Amazon Transportation

Amazon

Bellevue, WA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,079 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers


Job description

Amazon's Middle Mile Surface Research Science seeks an Applied Scientist to invent and build machine learning models that improve how Amazon plans and operates its transportation network.
Amazon's transportation network moves millions of truckloads of freight between vendors, warehouses, and customers using a fleet of trucks, trains, and airplanes, on time and at low cost. Operating it requires constant decisions about how to route, schedule, and balance capacity across the network, and our strategy is to make those decisions with science-driven technology. Because existing techniques rarely fit Amazon's scale and unique business needs, this role centers on inventing new approaches and algorithms.
As an Applied Scientist, you'll develop machine learning, forecasting, and prediction models and algorithms. Your first project will focus on trailer imbalance forecasting and safety stock optimization to improve our equipment re-balancing strategy, where you'll own the prediction models and grow your scope over time. Your models will impact business decisions worth billions of dollars and improve the delivery experience for millions of customers.
Key job responsibilities
- Design and develop machine learning, forecasting, and other prediction models that enhance our optimization and planning systems.
- Build models and algorithms from prototype to production-level systems.
- Translate ambiguous business problems into modeling approaches, and drive the technical design with product, engineering, and operations partners.
- Influence key business decisions through rigorous modeling and analysis.
- Communicate results and recommendations to scientific and business audiences.
A day in the life
- Analyze data to investigate a business problem or model performance and identify improvements
- Brainstorm new algorithmic strategies or business opportunities with fellow scientists
- Leverage GenAI to build and test your new model features
- Run a simulation or experiment to evaluate your model's performance
- Meet with product and tech partners to review project requirements, data, design, or other project decisions
- Review code changes or a design document from a fellow scientist or engineers
- Write and present a paper documenting algorithm features, results, and recommendations
About the team
Middle Mile Surface Research Science builds the models and algorithms that plan and operate Amazon's middle mile network. Our work spans operations research, optimization, and machine learning. We work on vehicle route planning, capacity planning, scheduling, network design, transit-time prediction, demand forecasting, and equipment re-balancing. Our team of about ten scientists is part of a broader science organization whose scientists bring deep expertise in machine learning and optimization. We optimize decisions worth billions of dollars and reach millions of customers.
BASIC QUALIFICATIONS
- PhD, or Master's degree and 4+ years of science, technology, engineering or related field experience
- Experience building machine learning models or developing algorithms for business application
- 1+ years of programming in Java, C++, Python or related language experience
- Experience in standard machine-learning and statistical modeling tools and techniques (e.g. random forests, gradient-boosted regression, LASSO, logistic regression)
PREFERRED QUALIFICATIONS
- Experience in professional software development
- Experience with forecasting and statistical analysis
- Experience in optimization mathematics such as linear programming and nonlinear optimization
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Bellevue - 142,800.00 - 193,200.00 USD annually

What Amazon employees say

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About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US