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Materials Informatics Jobs in Seattle, WA (NOW HIRING)

Olympic College

Nursing Adjunct

Bremerton, WA

$1.0K/wk

Model the use of Nursing Informatics and Information Literacy. * Demonstrate excellent ... materials: * Olympic College Online Application * Resume * Cover Letter - in your cover letter ...

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All JobsMaterials Informatics JobsMaterials Informatics Jobs in Seattle, WA

Materials Informatics information

See Seattle, WA salary details

$48.4K

$97.4K

$142.3K

How much do materials informatics jobs pay per year?

As of Jun 23, 2026, the average yearly pay for materials informatics in Seattle, WA is $97,426.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,500.00 and $113,800.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Materials Informatics position, and why are they important?

To thrive in Materials Informatics, you need a strong background in materials science combined with expertise in data analysis, machine learning, and computational modeling, typically supported by an advanced degree in a related field. Familiarity with programming languages such as Python, data visualization tools, scientific databases, and materials-specific simulation software is essential. Strong problem-solving abilities, clear communication, and the ability to work collaboratively across interdisciplinary teams are valuable soft skills for this role. These competencies are crucial for transforming complex materials data into actionable insights, accelerating materials discovery and innovation.

What is a Materials Informatics job?

A Materials Informatics job involves using data science, machine learning, and computational techniques to analyze and predict material properties, accelerating material discovery and optimization. Professionals in this field work at the intersection of materials science and informatics, leveraging large datasets and models to guide experiments and improve material performance. Common responsibilities include database management, algorithm development, and collaboration with researchers to interpret results and apply insights to real-world applications.

What are typical daily responsibilities for someone working in Materials Informatics?

Professionals in Materials Informatics commonly spend their days analyzing large-scale experimental and simulation data, developing and testing machine learning models, and collaborating closely with materials scientists, engineers, and software developers. They are often involved in designing data pipelines, automating analysis workflows, cleaning and curating materials datasets, and presenting their findings to both technical and non-technical stakeholders. Regular tasks may also include documenting methodologies, publishing research outcomes, and participating in team meetings to align projects with organizational goals. By working at the intersection of data science and materials research, they help accelerate the discovery and development of new materials.

What are the most commonly searched types of Materials Informatics jobs in Seattle, WA? The most popular types of Materials Informatics jobs in Seattle, WA are:
What are popular job titles related to Materials Informatics jobs in Seattle, WA? For Materials Informatics jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Materials Informatics jobs in Seattle, WA look for? The top searched job categories for Materials Informatics jobs in Seattle, WA are:
Materials Informatics jobs near you
Infographic showing various Materials Informatics job openings in Seattle, WA as of June 2026, with employment types broken down into 63% Full Time, and 37% Contract. Highlights an 89% In-person, and 11% Remote job distribution, with an average salary of $97,426 per year, or $46.8 per hour.
Automation Engineer, Materials Research Science

Automation Engineer, Materials Research Science

Meta

Redmond, WA

Full-time

Posted 6 days ago

Meta rating

7.5

Company rating: 7.5 out of 10

Based on 43 frontline employees who took The Breakroom Quiz

123rd of 191 rated software companies

Job description

Meta Reality Labs is seeking an engineer to advance materials research capabilities for next-generation wearables hardware. In this role, you will design, build, and operate the automation backbone of an autonomous materials discovery lab — connecting AI agents, robotic work-cells, and scientific instruments into a seamless, closed-loop pipeline. Working at the intersection of lab automation, agentive AI, and computational materials science, this role translates scientific workflows into production-grade software that compresses a discovery cycle from years into weeks, accelerating the development of novel materials for next-generation wearable devices and robotics.
Automation Engineer, Materials Research Science Responsibilities:
  • Define the long-term technical roadmap for laboratory automation systems, integrating robotic sample handling, automated metrology instruments, and data acquisition pipelines
  • Architect and own the end-to-end automation infrastructure for high-throughput materials characterization workflows, including optical, mechanical, and electrical property testing of wearable device materials
  • Collaborate with scientists, hardware engineers, and product teams to translate experiments and lab workflows into clear integration specifications, data models, and scalable automation solutions
  • Work with integrators and vendors to design, build, and commission automated workcells for materials R&D (process development, characterization, property testing, etc.)
  • Build and maintain middleware services that connect instruments, robots, and sensors to laboratory information management systems
  • Develop instrument drivers and automation scripts that generate command sequences and invoke vendor APIs/SDKs to orchestrate lab workflows end-to-end
  • Collaborate with AI and data scientists to tightly integrate the autonomous lab with LLM-based multi-agent systems for experiment planning, analysis, and decision-making
  • Design and implement data pipelines that capture, validate, and store experimental metadata to ensure data integrity and reproducibility across the discovery pipeline
  • Evaluate and benchmark automation performance — measuring throughput, reliability, error rates, and turnaround time of automated experimental workflows
  • Contribute to internal tooling, documentation, and best practices that enable the broader team to leverage automation capabilities
  • Drive the adoption of design-of-experiments methodologies and statistical process control within automated materials screening workflows
  • Define standards and best practices for automation system reliability, calibration, and data integrity across the materials research organization
  • Provide technical guidance to other engineers on automation architecture decisions, instrumentation integration patterns, and software design for laboratory systems
  • Evaluate and integrate emerging laboratory automation technologies, robotics platforms, and scientific instrumentation relevant to materials research

Minimum Qualifications:
  • Ph.D. degree in Electrical Engineering, Computer Science, Mechanical Engineering, Control Engineering, Materials Science, or relevant field, and/or equivalent practical experience
  • 6+ years of experience in lab automation, systems integration, or industrial automation software and/or relevant technical experience
  • Proficiency in Python, with experience writing production-quality automation and integration code
  • Hands-on experience with lab automation platforms (e.g., liquid handlers, robotic arms, automated characterization tools)
  • Experience with laboratory information management systems, electronic lab notebooks, or manufacturing execution systems
  • Demonstrated ability to translate scientific or manufacturing workflows into reliable, automated processes
  • Experience architecting scalable automation platforms for materials characterization or physical science research environments
  • Experience with statistical analysis and data pipeline design for high-throughput experimental datasets

Preferred Qualifications:
  • A track record of commissioning or bringing up complex lab, pilot, or manufacturing equipment
  • Familiarity with APIs, databases, and enterprise software integration patterns
  • Experience defining automation strategy and technical standards at an organizational level within a research or advanced hardware development environment
  • Familiarity with computational chemistry or materials science tools (DFT, MD, LAMMPS, ASE) and high-performance computing (HPC) environments
  • Experience with retrieval-augmented generation (RAG), knowledge graphs, or scientific literature mining in the context of lab systems
  • Publications or demonstrated accomplishments recognized in the field of laboratory automation or materials informatics
  • Experience with materials relevant to wearables hardware, such as optical coatings, waveguide materials, display substrates, or flexible electronics
  • Experience integrating robotic platforms with laboratory information management systems (LIMS) or material databases
  • Experience integrating AI/ML models or LLM-based agent frameworks into physical lab workflows
  • Experience with data historians, or real-time supervisory dashboards
  • Knowledge of industrial communication protocols
  • Familiarity with design-of-experiments frameworks and machine learning approaches applied to accelerated materials discovery

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$184,000/year to $257,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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