{"id":4186070,"url":"https://alion.io/job/weekday-mechanical-engineer-ai-expert-full-time-us","title":"Mechanical Engineer, AI Expert (Full-Time, US)","company":{"id":7097,"name":"Weekday","domain":"weekday.works","url":"https://alion.io/company/weekday","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"B","score":80,"open_postings":117,"ghost_share":0,"stale_share":0.983,"repost_share":0,"time_to_fill_p50_days":5,"computed_at":"2026-11-12T10:38:37Z"}},"role":"Industrial Engineering","role_family":"Industrial Engineering","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":60,"max":90,"currency":"USD","period":"hour","gross":null,"usd_annual":180000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Abaqus","optional":false},{"name":"ANSYS","optional":false},{"name":"AutoCAD","optional":false},{"name":"CATIA","optional":false},{"name":"GD&T","optional":false},{"name":"MATLAB","optional":false},{"name":"Siemens NX","optional":false},{"name":"SolidWorks","optional":false}],"status":"live","first_seen_at":"2026-11-12T18:17:58Z","employer_posted_date":"2026-11-12","last_verified_at":"2026-11-12T18:17:58Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"This role is for one of our clients\nCompensation: $60-$90 per hour\nLocation: Remote (United States)\nEmployment Type: Full-Time, W-2\nWork Commitment: 40 hours per week\nInitial Engagement: 2-3 months, with a strong possibility of extension\nJob Overview\nWe are seeking experienced Mechanical Engineers with strong, hands-on industry expertise to contribute to the development and evaluation of next-generation AI models. This opportunity is designed for practicing engineering professionals who have independently owned real-world designs, analyses, and mechanical systems and can apply sound engineering judgment to complex technical challenges.\nIn this role, you will work directly with research and program management teams at a leading AI lab to improve how advanced AI models understand, reason about, and solve practical mechanical engineering problems. Your expertise will help shape high-quality training datasets, develop technical benchmarks, create reference solutions, and establish evaluation standards that measure the accuracy and reliability of AI-generated engineering outputs.\nThis is a full-time, fully remote W-2 employment opportunity within the United States. You will be provided with client-issued accounts and equipment and will collaborate with the client's internal research teams using their tools and workflows.\nRequirements\nKey Responsibilities\nTechnical Review and Quality Assurance: Evaluate mechanical engineering tasks and AI-generated solutions, identifying incorrect assumptions, missing constraints, unit and tolerance errors, unsafe design decisions, and technically unsound recommendations.\nInstruction Specifications and Reference Solutions: Develop clear technical instructions, create detailed reference solutions, and design engineering tasks that reflect real-world industry practices and problem-solving requirements.\nBenchmark and Evaluation Development: Build challenging engineering tasks and evaluation datasets across mechanical design, thermal and fluid systems, structural and stress analysis, manufacturing engineering, and control systems.\nEngineering Validation: Assess whether AI-generated solutions meet practical engineering requirements, design constraints, safety considerations, and applicable industry standards.\nTechnical Feedback: Provide precise, structured written feedback to improve the accuracy, consistency, and practical relevance of AI model outputs.\n Research Collaboration and Calibration: Work closely with AI researchers and subject-matter experts from adjacent disciplines to establish consistent evaluation standards and translate practical engineering judgment into measurable criteria.\nRequired Qualifications\nBachelor's degree or higher in Mechanical Engineering or a closely related engineering discipline.\nMinimum of 5 years of hands-on professional mechanical engineering experience in an industry environment.\nRelevant experience in one or more of the following areas:\nMechanical product design and development.\nThermal engineering and fluid systems.\nHVAC and industrial systems.\nStructural engineering and stress analysis.\nManufacturing and production engineering.\nAutomotive and aerospace engineering.\nEnergy systems.\nRobotics and medical devices.\nDemonstrated ownership of real-world engineering projects, such as component or system design, FEA or CFD analysis, preparation and release of engineering drawings and specifications, design reviews, product testing, validation, and production.\nProficiency with commonly used engineering tools and software, including SolidWorks, CATIA, Siemens NX, Creo, AutoCAD, ANSYS, Abaqus, or MATLAB.\nFamiliarity with relevant engineering codes and standards, including ASME, ASTM, ISO, and Geometric Dimensioning and Tolerancing (GD&T) as per ASME Y14.5.\nClear career progression toward senior or lead engineering responsibilities.\nPractical experience using large language models (LLMs) in a professional environment, along with the ability to distinguish technically sound AI-generated responses from plausible but incorrect solutions.\nExcellent written communication skills and the ability to provide clear, detailed, and well-structured technical feedback.\nAbility to commit reliably to 40 hours per week for the initial engagement period.\nPreferred Qualifications\nProfessional Engineer (PE) license.\nExperience leading mechanical engineering projects or managing design, analysis, testing, and validation activities.\nExperience working with multidisciplinary engineering and research teams.\nFamiliarity with AI model evaluation, technical benchmark development, or engineering assessment frameworks.\nEmployment Details\nWork Arrangement: Fully remote within the United States.\nEmployment Type: Full-time, W-2 employment.\nWork Schedule: 40 hours per week.\nInitial Duration: 2-3 months.\nExtension: Strong possibility of extension based on performance and project requirements.\nEquipment and Access: Client-issued accounts and equipment will be provided.\nWork Environment: Direct collaboration with the client's research and program management teams, using internal tools and established 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