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Home Based Graduate Materials Science Jobs (NOW HIRING)

Socket.dev

Staff Scientist - Materials Science

Bothell, WA · On-site

$174.52 - $250.25/hr

This role is based at our Bothell, WA office, operating in a hybrid working model. Travel: Up to 5% ... home technology stipend. Details of participation in these benefit plans will be provided when a ...

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Mercor

Materials Scientist

Detroit, MI · On-site

$70 - $110/hr

Position: Materials Science Domain Expert Type: Contract Compensation: $70-$110/hour Location ... AI interview based on your resume * Submit form Resources & Support * For details about the ...

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How much do home based graduate materials science jobs pay per year?

As of Aug 21, 2026, the average yearly pay for home based graduate materials science in the United States is $123,973.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,500.00 and $167,000.00 per year, depending on experience, location, and employer.

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What states have the most Home Based Graduate Materials Science jobs?

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Home Based Graduate Materials Science jobs near you
Infographic showing various Home Based Graduate Materials Science job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 15% Part Time, and 7% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $123,973 per year, or $59.6 per hour.

Materials Science Ai Engineer

Cardinal Integrated Technologies Inc

Santa Clara, CA • On-site

Full-time

Re-posted 28 days ago

Job description

Job Summary:
Cardinal Integrated Technologies Inc is seeking a Materials Science AI Engineer to join their team in developing and supporting materials discovery and design. The ideal candidate will focus on building AI-based solutions and collaborating with scientists and engineers to integrate analytics into core R&D workflows.
Responsibilities:
• Design, develop and deploy multi-modal AI, ML, and hybrid physical-based models to solve ground-breaking material physics and design problems.
• Aggregate, process, transform and quality-control experimental and simulation data for modeling and analysis.
• Design, develop, and maintain data workflows to support materials informatics initiatives. Optimize data pipelines and model execution on parallel cloud systems (e.g., Azure, GCP, AWS).
• Collaborate with materials scientists, chemists, and software engineers to integrate analytics and predictive modeling into core R&D workflows.
• Document code, workflows, and best practices to support reproducible research.
• Apply AI and data analytics to optimize material synthesis and processing parameters in real-time, minimizing defects, improving consistency.
Qualifications:
Required:
• Strong proficiency in programming languages like Python and C++.
• Experience with machine learning and deep learning frameworks (e.g., PyTorch, TensorFlow).
• Experience with data cleansing, preprocessing, and feature engineering
• Graduate or undergraduate degree in Computer Science, Engineering, Applied Mathematics, or a related technical field.
• 2-4 years of work experience (depending on educational degree) in data science, AI, machine learning, or data engineering roles.
• A strong foundation in the principles of materials science is essential to understand the underlying science and set up meaningful problems for AI.
• Expert in Python and data science libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow or PyTorch).
• Expertise in use of cloud-based compute environments and tools for parallel or distributed computing.
• Strong problem-solving and communication skills.
Preferred:
• Design, develop and deploy multi-modal AI, ML, and hybrid physical-based models to solve ground-breaking material physics and design problems
Company:
We are a company of IT professionals who passionately believe that good quality products & services are delivered by great resources. Founded in 2013, the company is headquartered in Monmouth Junction, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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