Mechanical Engineer

Job Title: Mechanical Engineer

Job Type: Contractor

Location: Remote

Rate: 20$-50$ per task

Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.

Key Responsibilities:

• Analyze technical documents and extract key information relevant to your domain expertise

• Generate, review, and refine questions and solutions based on real-world mechanical engineering scenarios

• Collaborate with multidisciplinary teams to ensure accuracy and depth of data and analysis

• Provide detailed written and verbal feedback on document clarity, technical accuracy, and effectiveness

• Apply advanced subject matter knowledge to evaluate and solve complex engineering problems

• Work independently, managing your time to deliver high-quality outputs with minimal supervision

• Contribute to the continuous improvement of data quality and project processes

Required Skills and Qualifications:

• 2-6 years of professional or academic experience in mechanical engineering or a closely related field (lab, workplace, or academia)

• Strong reading comprehension skills, with proven ability to analyze and interpret technical documents

• Exceptional English communication skills, both written and verbal

• Demonstrated experience in creating or evaluating technical content, such as reports, studies, or problem sets

• Ability to work independently and efficiently, with excellent self-management

• High attention to detail and commitment to data accuracy

• Experience interfacing with technical documentation and performing analytical tasks

Preferred Qualifications:

• Advanced degree (Master’s or PhD) in Mechanical Engineering, Chemistry, Physics, or Biology

• Previous experience contributing to interdisciplinary or research-driven projects

• Familiarity with data-driven analysis or training data preparation

Required Skills

• mechanical engineering
• technical document analysis
• problem-solving
• written and verbal communication
• data analysis
• attention to detail
• self-management
• interdisciplinary collaboration
• technical content creation
• data quality assurance