Materials Science Domain Expert

This role is for one of our clientsCompensation: $70 - $110 per hourWe are seeking an experienced Materials Science Domain Expert to contribute to an advanced GenAI initiative focused on improving how AI systems understand, reason about, and solve complex materials science and materials engineering problems.Your technical expertise will be central to this role. You will evaluate materials science knowledge tasks and AI-generated outputs, develop detailed instructions and reference solutions, and create rigorous benchmarks that define what high-quality technical reasoning looks like.We are looking for a hands-on materials specialist with deep expertise in a specific area of materials science or engineering, rather than a broad generalist.This is a full-time engagement requiring 40 hours per week for an initial six-month period. You will collaborate closely with research and program teams and work within established technical workflows and enterprise tools.Location: Hybrid role based in the Bay Area, California. Candidates must currently live in the Bay Area and be available to work on-site multiple days per week when required. This is not a fully remote position. Candidates outside the Bay Area must be willing to relocate at their own expense before the engagement begins. Relocation assistance is not provided.RequirementsKey ResponsibilitiesTechnical Data Quality & EvaluationReview and assess materials science knowledge tasks and AI-generated technical outputs for accuracy, depth, scientific validity, and practical relevanceIdentify incomplete reasoning, unsupported structure-property relationships, incorrect technical assumptions, and conclusions that may appear convincing but fail expert-level scrutinyEvaluate whether AI-generated solutions align with established scientific principles, engineering practices, and real-world materials workflowsInstruction & Reference Solution DevelopmentWrite clear and comprehensive instruction specifications that define expected approaches and outcomes for materials science problemsDevelop high-quality reference or "golden" solutions for complex materials science and engineering scenariosCreate new technical tasks that accurately reflect how materials scientists and engineers approach real-world research, development, characterization, and optimization challengesBenchmark & Evaluation DevelopmentDesign challenging materials science tasks and evaluation datasets that test scientific reasoning and technical expertiseContribute to the development of materials-specific benchmarks, capabilities, and evaluation toolsEstablish meaningful criteria for assessing AI performance across different materials science and engineering applicationsExpert Calibration & CollaborationCollaborate with researchers and subject matter experts from related scientific and engineering disciplinesHelp maintain consistency and accuracy across evaluation standards and technical datasetsTranslate practical materials science expertise and professional judgment into explicit, structured, and teachable evaluation criteriaProvide precise written feedback to improve the technical quality and reliability of AI-generated solutionsCore QualificationsEducation: PhD in Materials Science, Materials Engineering, or a closely related discipline such as Chemistry, Chemical Engineering, Applied Physics, Metallurgy, or a related technical fieldA Master's degree with exceptional industrial or research depth may be considered for highly experienced candidatesExperience: At least 4 years of substantive research or industrial R&D experience in materials science, materials engineering, or a closely related fieldRelevant experience may come from a research university, national laboratory, industrial research organization, or materials-focused technology companyGraduate coursework or academic training alone does not satisfy the professional experience requirementDomain Expertise: Demonstrated specialization in at least one materials-focused area, such as:Energy storage and battery materialsSemiconductors and electronic materialsPolymers and soft matterStructural alloys and metallurgyMaterials characterization and microscopyComputational materials science and simulationNanomaterials and advanced materialsFunctional or engineered materialsSeniority: Demonstrated progression into a senior technical or research position, such as Senior Scientist, Staff Scientist, Research Lead, Principal Investigator, or senior industrial R&D leadershipProven ownership of research direction, technical programs, materials development initiatives, or significant research projectsResearch Record: Peer-reviewed publications, granted patents, technology development, or successful materials programs are strongly preferredAI Fluency: Hands-on professional experience using large language models or AI tools, along with the ability to distinguish technically rigorous reasoning from plausible but scientifically incorrect outputsAvailability: Ability to commit reliably to 40 hours per week for an initial six-month engagementLocation: Must reside in the Bay Area, California, and be able to work on-site multiple days per week when required. Candidates outside the area must be willing to relocate at their own expense. Relocation assistance is not providedExcellent written communication skills and the ability to provide precise, structured, and actionable technical feedbackPreferred QualificationsExperience working on multidisciplinary materials research involving chemistry, physics, engineering, or computational methodsFamiliarity with modern materials characterization techniques, simulation methodologies, or experimental workflowsExperience translating research findings into practical engineering or commercial applicationsBackground in advanced materials development, materials optimization, or technology commercializationExperience reviewing technical documentation, scientific research, engineering analyses, or AI-generated technical contentStrong interest in the application of artificial intelligence to scientific research and engineeringWhat You'll ContributeYou will help transform expert materials science knowledge into structured tasks, reference solutions, evaluation frameworks, and benchmarks for next-generation AI systems.Your expertise will help ensure that AI-generated materials science solutions are not merely fluent or convincing, but scientifically sound, technically rigorous, logically reasoned, and relevant to real-world research and engineering practice.Equal OpportunityWe are committed to providing equal employment opportunities to all qualified candidates. Employment decisions are made without regard to legally protected characteristics. Reasonable accommodations are available for qualified individuals throughout the application and hiring process.