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Ai For Science Jobs in Seattle, WA (NOW HIRING)

Ai2 is a non-profit AI research institute based in Seattle, focused on developing foundational AI ... science of deep learning, or efficient algorithms for deep learning. • The ability to own and ...

The R2L team is responsible for building the next generation supply chain for Amazon's world-class ... The R2L Science & AI team is the centralized data science and AI function serving all R2L business ...

The R2L team is responsible for building the next generation supply chain for Amazon's world-class ... The R2L Science & AI team is the centralized data science and AI function serving all R2L business ...

The R2L team is responsible for building the next generation supply chain for Amazon's world-class ... The R2L Science & AI team is the centralized data science and AI function serving all R2L business ...

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Showing results 1-20

Ai For Science information

See Seattle, WA salary details

$27.9K

$55.1K

$89.9K

How much do ai for science jobs pay per year?

As of Aug 20, 2026, the average yearly pay for ai for science in Seattle, WA is $55,070.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,800.00 and $59,200.00 per year, depending on experience, location, and employer.

What is AI for Science?

AI for Science refers to the application of artificial intelligence and machine learning techniques to accelerate scientific discovery and research. By leveraging large datasets, complex models, and advanced computational methods, AI helps scientists analyze data, identify patterns, simulate experiments, and make predictions across various scientific fields such as biology, chemistry, physics, and climate science. This approach can significantly speed up research, uncover new insights, and solve problems that were previously too complex or time-consuming for traditional methods.

How does collaboration typically work between AI for Science professionals and domain experts in research teams?

AI for Science professionals frequently work closely with experts in fields such as biology, chemistry, or physics to identify scientific problems that can benefit from machine learning techniques. Collaboration usually involves regular meetings to translate complex scientific challenges into data-driven models, sharing domain knowledge, and iteratively refining solutions. Effective communication and a willingness to bridge gaps between computational and scientific perspectives are essential. This interdisciplinary teamwork not only enhances the impact of AI solutions but also fosters ongoing learning and innovation.

What are the key skills and qualifications needed to thrive as an AI for Science specialist, and why are they important?

To thrive as an AI for Science Specialist, you need a strong background in computer science, mathematics, and scientific domains, often supported by advanced degrees (e.g., PhD or MSc) in relevant fields. Proficiency with machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools, and familiarity with high-performance computing environments are typically required. Critical thinking, interdisciplinary collaboration, and effective communication are crucial soft skills for translating scientific problems into AI solutions. These skills are vital for developing innovative models, ensuring research rigor, and enabling impactful scientific discoveries.

What is the difference between Ai For Science vs Data Scientist?

AspectAi For ScienceData Scientist
Required CredentialsDegree in Science, Computer Science, or related fields; knowledge of AI and machine learningDegree in Statistics, Computer Science, or related fields; strong programming skills
Work EnvironmentResearch labs, scientific institutions, tech companies focused on scientific applicationsCorporate, tech firms, finance, healthcare, and other industries analyzing data
Industry UsageApplied to scientific research, simulations, and experimental data analysisUsed for data analysis, predictive modeling, and business insights

Ai For Science focuses on applying AI techniques to scientific research and experiments, often requiring a background in science and specialized knowledge of AI. Data Scientists analyze large datasets across various industries to extract insights and build models. While both roles involve AI and data analysis, Ai For Science is more research-oriented within scientific contexts, whereas Data Scientists work across diverse sectors on data-driven decision making.

What job categories do people searching Ai For Science jobs in Seattle, WA look for?

The top searched job categories for Ai For Science jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Ai For Science jobs?

Cities near Seattle, WA with the most Ai For Science job openings:

Infographic showing various Ai For Science job openings in Seattle, WA as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 20% Part Time, and 4% Contract. Highlights an 77% Physical, 4% Hybrid, and 19% Remote job distribution, with an average salary of $55,070 per year, or $26.5 per hour.

Research Scientist, Agents for Science

Ai2

Seattle, WA • On-site

Full-time

Re-posted 7 days ago


Job description

Job Summary:
Ai2 is a non-profit AI research institute focused on developing foundational AI research and innovation. The Research Scientist will drive the development of AI systems with deep reasoning capabilities, lead foundational research, and shape the strategic direction of agentic systems.
Responsibilities:
• Contribute to Ai2’s open source research environment to innovate, study and advance the science of generative AI and agentic systems.
• Take a leading role in building artifacts and implementing software systems with real-world impact
• Author and present high-quality scientific technical reports, papers, and presentations
• Collaborate with and learn from team members across Ai2, including scientists and engineers
• Mentor early-career researchers and interns on their projects
• Develop collaborative relationships with relevant academic, industrial, government, and standards organizations
Qualifications:
Required:
• A PhD focusing on machine learning, reasoning, natural language processing, or a related area, with expertise in one or more of the following: reinforcement learning, experimental methodology, language models, the science of deep learning, or efficient algorithms for deep learning.
• The ability to own and pursue a research agenda to improve AI model reasoning capabilities.
• Enthusiasm for collaboration and teamwork on ambitious projects aligned with company goals.
• Experience leading a team to solve analytical problems.
• Contributions to open-source research libraries and an interest in continuing such work.
Company:
We are a Seattle-based non-profit AI research institute founded in 2014 by the late Paul Allen. Founded in 2014, the company is headquartered in Seattle, USA, with a team of 201-500 employees. The company is currently Growth Stage.