[Hiring] Mechanical Engineer, AI Expert @Weekday AI

Role Description

We 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.

In 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.

Key Responsibilities

• Technical 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.
• Instruction 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.
• Benchmark 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.
• Engineering Validation: Assess whether AI-generated solutions meet practical engineering requirements, design constraints, safety considerations, and applicable industry standards.
• Technical Feedback: Provide precise, structured written feedback to improve the accuracy, consistency, and practical relevance of AI model outputs.
• 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.

Qualifications

• Bachelor's degree or higher in Mechanical Engineering or a closely related engineering discipline.
• Minimum of 5 years of hands-on professional mechanical engineering experience in an industry environment.
• Relevant experience in one or more of the following areas:
  • Mechanical product design and development.
  • Thermal engineering and fluid systems.
  • HVAC and industrial systems.
  • Structural engineering and stress analysis.
  • Manufacturing and production engineering.
  • Automotive and aerospace engineering.
  • Energy systems.
  • Robotics and medical devices.
• Demonstrated 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.
• Proficiency with commonly used engineering tools and software, including SolidWorks, CATIA, Siemens NX, Creo, AutoCAD, ANSYS, Abaqus, or MATLAB.
• Familiarity with relevant engineering codes and standards, including ASME, ASTM, ISO, and Geometric Dimensioning and Tolerancing (GD&T) as per ASME Y14.5.
• Clear career progression toward senior or lead engineering responsibilities.
• Practical 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.
• Excellent written communication skills and the ability to provide clear, detailed, and well-structured technical feedback.
• Ability to commit reliably to 40 hours per week for the initial engagement period.

Preferred Qualifications

• Professional Engineer (PE) license.
• Experience leading mechanical engineering projects or managing design, analysis, testing, and validation activities.
• Experience working with multidisciplinary engineering and research teams.
• Familiarity with AI model evaluation, technical benchmark development, or engineering assessment frameworks.

Employment Details

• Work Arrangement: Fully remote within the United States.
• Employment Type: Full-time, W-2 employment.
• Work Schedule: 40 hours per week.
• Initial Duration: 2–3 months.
• Extension: Strong possibility of extension based on performance and project requirements.
• Equipment and Access: Client-issued accounts and equipment will be provided.
• Work Environment: Direct collaboration with the client's research and program management teams, using internal tools and established workflows.
• Engagement Structure: This is a structured, role-based employment opportunity rather than a freelance or project-based engagement.