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

Axon

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 Sep 2, 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 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 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 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:

Scientific Machine Learning jobs near you

Machine Learning / Data Scientist

Docugami

Kirkland, WA • On-site

Full-time

Medical, PTO

Re-posted 24 days ago

Job description

Docugami uses powerful artificial intelligence to unlock the information contained in highly varied, unstructured business documents. Business users, without IT or development projects, can immediately create custom analysis of vital document content and information from large batches of contracts, can assist users in creating new documents more efficiently and consistently, and can automatically connect information from within documents to other business systems.
Docugami started with years of R&D, and has received a $10M seed round of VC funding as well as multiple endorsements from industry leaders and publications. The founders are seasoned ex-Microsoft engineers and leaders, some already well known in the software industry for their record of building and running $1B+ innovative software product businesses.
Docugami is looking for Machine Learning, Data Science and Math PhD researchers to work alongside our world-renowned science and engineering team to create a revolutionary product. We are looking for experienced researchers to work with our luminary science advisors on major scientific breakthroughs.
You will love this job if:
  • You love solving really challenging problems
  • You seek opportunities to see your research deployed in practice to solve real world problems and impact millions of users
  • You enjoy working at the very cutting edge of R&D
  • You want to experience an early stage startup

What you'll be responsible for:
  • Proposing solutions to the different science problems in an evolving environment
  • Collaborating with engineering and product leadership to plan and prioritize a long-term roadmap of science breakthroughs
  • Working with the engineering team who will be responsible for integrating and deploying your work in production
  • Conducting regular internal science reviews and educational sessions for the team
  • Working with our partners in academia to stay at the very forefront of R&D in our space

What we look for in a candidate:
  • More than five years of experience after completing PhD, or equivalent demonstrable industry experience
  • PhD (or equivalent experience) in areas like computer science, mathematics, statistics, electrical engineering, or related fields
  • Deep and up-to-date experience with some of the following: natural language processing (NLP), machine translation, self-supervised learning, active learning, computer vision, statistics, causal inference, and other related disciplines
  • Programming skills and familiarity of modern ML frameworks
  • Research track demonstrated by top-level journal and conference publications
  • Strong problem-solving and self management skills
  • Passion for technical and scientific excellence
  • Strong communication skills and capacity to report and disseminate results

Perks:
  • Competitive salary with stock options
  • Healthcare plan
  • Competitive vacation and leave policy
  • Unlimited in-house healthy snacks & drinks
  • Work closely with a cross-functional team of highly motivated folks with a unique range of startup, big enterprise, scientific, engineering, sales & marketing experience
  • Vibrant and inclusive company culture with frequent team-building events

About Us:
Docugami is a Seattle-area document engineering startup that transforms how businesses create and manage documents for greater productivity, compliance, and insight using breakthrough artificial intelligence. Founded in March 2018 by former senior engineering leaders from Microsoft, Docugami harnesses a wide range of artificial intelligence techniques, including natural language processing, image recognition, declarative markup, and other approaches, to enable businesses of all sizes to radically improve how they create and manage documents for greater insight, efficiency, and business impact.
Learn more at www.docugami.com
We welcome people of different backgrounds, experiences, abilities and perspectives and are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We are committed to an inclusive and diverse team.

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