<p><strong>Materials Science Domain Expert</strong></p><p><br></p><p><strong>Position:</strong> <strong>Materials Science Domain Expert</strong></p><p><br></p><p><strong>Type:</strong> <strong>Full-Time W-2 Employment</strong></p><p><br></p><p><strong>Compensation:</strong> <strong>$70–$110/hour</strong></p><p><br></p><p><strong>Location:</strong> <strong>Hybrid</strong></p><p><br></p><p><strong>About the Opportunity</strong></p><p>Cincinnatus LLC is hiring a senior <strong>Materials Science Domain Expert</strong> to work directly with the research and program management teams of a leading AI lab. The role focuses on improving how frontier AI models reason about real-world materials science and materials engineering problems.</p><p>Your materials expertise will be central to the role. You will evaluate the quality of materials science knowledge-work tasks and model outputs, create detailed instruction specifications and gold-standard solutions, and develop benchmarks that measure whether AI systems are genuinely improving.</p><p>This is a <strong>full-time W-2 employment position with Cincinnatus LLC</strong>, with the opportunity to be placed within a leading AI lab's extended workforce. You will receive client-issued accounts and equipment and work within the client's tools alongside their research teams.</p><p>This is a <strong>hybrid, non-remote position</strong>. Candidates must currently live in the Bay Area and be able to work on-site with the client's team multiple days each week when required. Candidates outside the Bay Area must be willing to relocate at their own expense before the engagement begins. <strong>Relocation assistance is not provided.</strong></p><p><strong>Responsibilities</strong></p><ul><li>Review and evaluate the quality of materials science knowledge-work tasks and AI-generated outputs.</li><li>Identify missing behaviors, weak reasoning, unsupported structure-property claims, and technically inaccurate conclusions.</li><li>Assess whether AI-generated answers can withstand professional materials science and engineering scrutiny.</li><li>Write detailed instruction specifications that define expected approaches and evaluation standards.</li><li>Develop gold-standard solutions for complex materials science problems.</li><li>Create new materials science tasks that accurately reflect real-world professional workflows.</li><li>Design challenging evaluation sets and domain-specific benchmarks for AI model assessment.</li><li>Help develop materials-specific capabilities, skills, and tools in collaboration with AI research teams.</li><li>Work with researchers and specialists in adjacent technical disciplines to maintain consistent evaluation standards.</li><li>Translate expert materials science judgment and tacit knowledge into explicit, teachable criteria.</li><li>Provide precise, structured written feedback on model performance and technical reasoning.</li></ul><p><strong>Required Qualifications</strong></p><ul><li><strong>PhD in Materials Science, Materials Engineering, or a closely related discipline</strong>, such as:</li><li>Chemistry</li><li>Chemical Engineering</li><li>Applied Physics</li><li>Metallurgy</li><li>A <strong>Master's degree with exceptional industrial depth</strong> may be considered.</li><li>At least <strong>4 years of substantive research or industrial R&D experience</strong> in materials science or materials engineering.</li><li>Experience at a <strong>research university, national laboratory, or industrial research organization</strong>.</li><li>Graduate coursework alone does not count toward the required experience.</li><li>Demonstrated specialization in at least one materials science area.</li><li>Clear progression to a senior-level position with meaningful ownership of research direction.</li><li>Hands-on professional use of <strong>large language models</strong>.</li><li>Ability to distinguish technically well-reasoned answers from plausible but incorrect AI-generated responses.</li><li>Excellent written communication skills.</li><li>Ability to provide precise, well-structured technical feedback.</li><li>Availability to commit <strong>40 hours per week</strong> for an initial <strong>6-month engagement</strong>.</li><li>Must currently live in the <strong>Bay Area, California</strong>, or be willing to relocate there at personal expense.</li><li>Must be able to work on-site with the client multiple days per week when required.</li></ul><p><strong>Preferred Qualifications</strong></p><ul><li>Peer-reviewed publications in materials science or related disciplines.</li><li>Granted patents or demonstrated ownership of significant materials programs.</li><li>Experience developing or evaluating technical benchmarks.</li><li>Experience translating complex technical expertise into structured evaluation criteria.</li><li>Experience collaborating across materials science, chemistry, physics, engineering, or AI research teams.</li><li>Demonstrated leadership in research direction, technical strategy, or industrial R&D.</li></ul><p><strong>Key Areas of Expertise</strong></p><p>Candidates should have genuine specialization in at least one of the following areas:</p><ul><li>Energy storage and battery materials</li><li>Semiconductor and electronic materials</li><li>Polymers and soft matter</li><li>Structural alloys and metallurgy</li><li>Materials characterization and microscopy</li><li>Computational materials science and simulation</li><li>Materials engineering and industrial R&D</li><li>Materials-property relationships and technical analysis</li></ul><p><strong>Seniority Expectations</strong></p><p>Strong candidates may have progressed into roles such as:</p><ul><li>Senior Scientist</li><li>Staff Scientist</li><li>Research Lead</li><li>Principal Investigator</li><li>Senior Industrial R&D Scientist</li><li>Comparable senior materials science or engineering leadership roles</li></ul><p>The role requires <strong>real ownership of research direction</strong>, not simply participation in graduate-level research.</p><p><strong>Compensation</strong></p><ul><li><strong>$70–$110 per hour</strong></li><li>Full-time W-2 employment through <strong>Cincinnatus LLC</strong>.</li><li>Initial engagement of approximately <strong>6 months</strong>.</li><li>Expected commitment of <strong>40 hours per week</strong>.</li><li>Client-issued accounts and equipment provided for the engagement.</li></ul><p><strong>Location & Work Arrangement</strong></p><ul><li><strong>Bay Area, California</strong></li><li><strong>Hybrid — not remote</strong></li><li>On-site collaboration with the client's team may be required multiple days each week.</li><li>Candidates currently outside the Bay Area must relocate before the engagement begins.</li><li><strong>Relocation assistance is not provided.</strong></li></ul><p><strong>About Cincinnatus LLC</strong></p><p>Cincinnatus LLC is an enterprise staffing company that partners with leading technology companies to source and employ highly skilled professionals for contingent and contract-based opportunities.</p><p>Cincinnatus serves as the employer of record, providing <strong>W-2 employment, payroll, benefits, and compliance</strong>, while placing employees directly within client teams to support high-impact initiatives.</p><p>These positions are structured as role-based employment rather than freelance or project-based work, with part-time or full-time commitments and integration into standard enterprise workflows.</p><p>Cincinnatus LLC is legally separate from Mercor. While opportunities may be discovered through Mercor's platform, employment, onboarding, payroll, and benefits are administered by <strong>Cincinnatus LLC</strong>.</p><p><strong>Eligibility</strong></p><ul><li>Must meet the required education and professional experience criteria.</li><li>Must demonstrate genuine specialization in materials science or a closely related discipline.</li><li>Must have professional experience in research or industrial R&D.</li><li>Must be proficient in written technical communication.</li><li>Must have professional experience using large language models.</li><li>Must be available for <strong>40 hours per week</strong> for the initial engagement.</li><li>Must live in the <strong>Bay Area, California</strong>, or be willing to relocate at personal expense.</li><li>Must be able to meet the hybrid on-site requirements.</li></ul><p><strong>Equal Employment Opportunity</strong></p><p>Cincinnatus LLC is an Equal Employment Opportunity employer. The company considers qualified applicants without regard to legally protected characteristics and provides reasonable accommodations to qualified individuals throughout the application process.</p>