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Salary
$120k – $180k per year
Location
Remote (United States)
Seniority
Senior
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 12, 2026. First seen by Alion on Nov 12, 2026. Weekday scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Weekday is an Indian recruitment company that sources software engineers through referrals from other engineers rather than through job advertisements or agency databases. Its model pays working engineers to vouch for former colleagues they rate, turning informal knowledge about who is genuinely good into a searchable candidate pool that companies can hire from. Based in Bengaluru and backed by Y Combinator, the platform has layered AI screening and outbound sourcing on top of that referral network, and sells to startups and technology companies hiring in the Indian market.
Backed by Y Combinator

This role is for one of our clients

Compensation: $60-$90 per hour

Location: Remote (United States)

Employment Type: Full-Time, W-2

Work Commitment: 40 hours per week

Initial Engagement: 2-3 months, with a strong possibility of extension

Job Overview

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.

This 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.

Requirements

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.

Required 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.
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