Materials Science Engineer - AI Trainer

Job not on LinkedIn

July 8

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Logo of Invisible Technologies Inc.

Invisible Technologies Inc.

Artificial Intelligence • SaaS • Enterprise

Invisible Technologies Inc. is a rapidly growing company that integrates world-leading AI with global human talent to enable AI adoption for enterprises. By combining artificial intelligence with human expertise in an integrated platform, Invisible Technologies focuses on training AI models, automating processes, and enhancing digital operations. The company's services include AI training, enablement, and intelligent operations solutions, catering to various industries such as financial services, healthcare, eCommerce, and technology. With significant growth recognized by the Deloitte Technology Fast 500 in 2024, Invisible Technologies helps organizations achieve transformational outcomes and significant ROI through expert process automation and AI solutions.

📋 Description

• Are you a materials science expert eager to shape the future of AI? • Large‑scale language models are evolving from clever chatbots into powerful engines of scientific discovery. • That training data begins with you—we need your expertise to help power the next generation of AI. • You’ll challenge advanced language models on topics like phase transformations, microstructure-property relationships, materials characterization techniques (XRD, SEM, TEM), thermal analysis, additive manufacturing, materials failure analysis, and sustainability in materials engineering—documenting every failure mode so we can harden model reasoning. • On a typical day, you will converse with the model on lab scenarios and theoretical materials science questions, verify factual accuracy and logical soundness, capture reproducible error traces, and suggest improvements to our prompt engineering and evaluation metrics. • Ready to turn your materials science expertise into the knowledge base for tomorrow’s AI? Apply today and start teaching the model that will teach the world.

🎯 Requirements

• A PhD in materials science, materials engineering, or a closely related physical science field is ideal. • Peer‑reviewed publications, lab-based testing, product design using advanced materials, or applied research signal fit. • Clear, metacognitive communication—“showing your work”—is essential.

🏖️ Benefits

• Company‑sponsored benefits such as health insurance and PTO do not apply.

Apply Now

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