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

Machine Learning Engineer

Bellevue, WA ยท On-site +1

$117K - $152K/yr

Bachelor's degree in Computer Science, Machine Learning, Systems, or a related field * Strong foundation in machine learning systems, distributed systems, or large-scale data processing (through ...

Machine Learning Engineer

Seattle, WA ยท On-site

$120K - $180K/yr

Collaborate with data scientists and flight software engineers to integrate AI capabilities into ... Proven experience deploying machine learning models into production. * Strong software engineering ...

Work closely with other engineering teams, data scientists, and the marketing team to integrate machine learning models into the product and ensure they meet business requirements. Present results to ...

Study and transform data science prototypes * Design machine learning systems * Research and ... implement appropriate ML algorithms and tools * Develop machine learning applications according to ...

Study and transform data science prototypes * Design machine learning systems * Research and ... implement appropriate ML algorithms and tools * Develop machine learning applications according to ...

Work closely with other engineering teams, data scientists, and the marketing team to integrate machine learning models into the product and ensure they meet business requirements. Present results to ...

Responsibilities : โ€ข Study and transform data science prototypes โ€ข Design machine learning systems โ€ข Research and implement appropriate ML algorithms and tools โ€ข Develop machine learning ...

Machine Learning Manager

Seattle, WA ยท On-site

$180K - $250K/yr

Undergraduate or graduate degree in computer science or similar technical field * 4+ years experience as a machine learning engineer, with experience in training large deep learning models and ...

AI & Machine Learning Engineer

Seattle, WA ยท On-site

$130K - $156K/yr

We Focus on Java /Full stack/Devops and Data Science /Data Engineers/Data analysts/BI Analysts/ Machine learning/AI candidates Ideal Candidates: Recent grads in CS, Engineering, Math, or Statistics ...

Undergraduate or graduate degree in computer science or similar technical field * 4+ years experience as a machine learning engineer, with experience in training large deep learning models and ...

This involves developing sophisticated machine learning and large language models (LLMs) to ... You will also work with researchers and data scientists to develop, fine-tune, and evaluate domain ...

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Scientific Machine Learning information

See Seattle, WA salary details

$15

$35

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How much do scientific machine learning jobs pay per hour?

As of Aug 5, 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 cities near Seattle, WA are hiring for Scientific Machine Learning jobs? Cities near Seattle, WA with the most Scientific Machine Learning job openings:

Machine Learning Engineer

Unitytech

Bellevue, WA โ€ข On-site, Remote

$117K - $152K/yr

Full-time

Medical, Life, Retirement, PTO

Re-posted 3 days ago


Job description

The opportunity
Unity Vector builds an offline ML platform that powers insight, experimentation, attribution, and AI-driven decision-making across the company.

Our systems operate at scale across batch and streaming data, supporting analytics, product intelligence, machine learning pipelines, and business operations. As data volume and complexity grow, our platform enables large-scale model training, feature generation, and experimentation workflows that power production ML systems.

We're looking for a Machine Learning Engineer to join our Offline Infrastructure team. This is an ideal role for a recent university graduate who is excited to work on large-scale systems and apply research-driven thinking to real-world machine learning problems.

You'll help build and evolve the infrastructure that powers training data generation, ML workflows, and distributed model training. Working closely with experienced engineers and researchers, you'll contribute to systems that ensure our ML pipelines are reliable, scalable, and efficient.

This role offers the opportunity to bridge research and production-translating advanced ideas into systems that operate at scale.

What you'll be doing

  • Build and maintain data pipelines that generate training datasets for machine learning models and experimentation
  • Contribute to infrastructure that supports distributed training workflows (e.g., PyTorch, Ray)
  • Work with workflow orchestration tools (e.g., Airflow, Flyte, or similar) to support multi-stage ML pipelines
  • Improve reproducibility and reliability through dataset validation, monitoring, and testing
  • Partner with ML engineers to support experimentation and model iteration
  • Help optimize performance and efficiency across data processing and training systems
  • Contribute to the evolution of our offline ML platform architecture as it scales

What we're looking for

  • Bachelor's degree in Computer Science, Machine Learning, Systems, or a related field
  • Strong foundation in machine learning systems, distributed systems, or large-scale data processing (through research or projects)
  • Experience with Python and working with data-intensive workloads
  • Familiarity with ML frameworks (e.g., PyTorch, TensorFlow) and/or distributed systems (e.g., Ray, Spark)
  • Experience (academic or applied) with data pipelines, model training workflows, or large datasets
  • Strong problem-solving skills and ability to translate research ideas into practical systems
  • Interest in building scalable, reliable infrastructure for machine learning
  • Nice to Have
  • Experience with workflow orchestration systems (Airflow, Flyte, etc.)
  • Exposure to large-scale data platforms (data lakes, warehouses, streaming systems)
  • Publications or research in ML systems, distributed systems, or related areas

Additional information

  • Relocation support is not available for this position
  • Work visa/immigration sponsorship is not available for this position

Base Salary Range: We determine the base salary range for this role based on your primary work location:

Mountain View, SF/Bay: $117,000 - $152,000 gross USD
Bellevue, Seattle, NYC, Remote CA: $104,100 - $135,300 gross USD

This range reflects the anticipated base salary for this position. Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount will depend on several factors, including geographic location and the candidate's relevant experience, professional background, and skill set.


Benefits


At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.


Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.


While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program


Life at Unity


Unity [NYSE: U] is the world's leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D - closing the gap between ideas and reality. For more information, please visit www.unity.com.


Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.


Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.


This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.


Headhunters and recruitment agencies may not submit resumes/CVs through this Web site or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.


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