Mercor
[Hiring] AI Tutor – Industrial and Systems Engineering Specialist @Mercor
Mercor, Germantown, Ohio, United States
Oct 25, 2025 - Mercor is hiring a remote AI Tutor – Industrial and Systems Engineering Specialist.
Salary: $90,000 - $200,000 usd yearly. Location: USA. This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description
Mercor is partnering with a leading AI research organization to engage professionals with advanced expertise in industrial and systems engineering. This full-time opportunity invites engineers and researchers to help train and refine AI models capable of understanding, analyzing, and optimizing complex systems and workflows. As an AI Tutor – Industrial and Systems Engineering Specialist , you will play a key role in advancing the development of AI systems by providing high-quality inputs, annotations, and expert feedback. Collaborate closely with technical teams to design new AI tasks Improve annotation tools Select challenging engineering problems that enhance model reasoning and performance Requires analytical precision, adaptability, and a strong interest in technology-driven innovation Qualifications
Master’s or PhD in Industrial Engineering, Systems Engineering, or a closely related field Strong written and verbal communication skills in both professional and informal English Skilled in research, data analysis, and using engineering databases and online resources Excellent analytical, problem-solving, and organizational abilities Ability to work independently and exercise sound judgment in ambiguous scenarios Passion for technological progress and AI innovation in engineering applications Requirements
PhD in Industrial or Systems Engineering with hands‑on professional experience in the field Publications or research contributions in reputable engineering journals Teaching or tutoring experience in engineering, systems optimization, or applied sciences Prior work in AI data training, technical writing, or industrial research Experience with complex, real‑world engineering systems and processes Work Environment
Based in Palo Alto, CA (in-office, 5 days per week) or fully remote with strong self‑management skills U.S.-based applicants must reside outside of Wyoming and Illinois Typical hours: 9:00am–5:30pm PST during training, then aligned with your local timezone Remote workers must use a personal computer that meets one of the following requirements: a Chromebook, a Mac running macOS 11 or newer, or a Windows PC running Windows 10 or newer Reliable smartphone access is required Compensation & Benefits
Competitive pay ranging from $90,000 to $200,000 annually for U.S.-based professionals, depending on experience and location For international candidates, compensation ranges are available upon request Access to medical benefits, subject to your country of residence Supportive, high‑impact environment focused on advancing AI and engineering innovation Application Process
Submit your resume Complete a 20-minute introductory interview Selected candidates will move on to a focused engineering data evaluation exercise Finalists will participate in a team discussion and review of their expertise The full process typically concludes within one week
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Salary: $90,000 - $200,000 usd yearly. Location: USA. This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description
Mercor is partnering with a leading AI research organization to engage professionals with advanced expertise in industrial and systems engineering. This full-time opportunity invites engineers and researchers to help train and refine AI models capable of understanding, analyzing, and optimizing complex systems and workflows. As an AI Tutor – Industrial and Systems Engineering Specialist , you will play a key role in advancing the development of AI systems by providing high-quality inputs, annotations, and expert feedback. Collaborate closely with technical teams to design new AI tasks Improve annotation tools Select challenging engineering problems that enhance model reasoning and performance Requires analytical precision, adaptability, and a strong interest in technology-driven innovation Qualifications
Master’s or PhD in Industrial Engineering, Systems Engineering, or a closely related field Strong written and verbal communication skills in both professional and informal English Skilled in research, data analysis, and using engineering databases and online resources Excellent analytical, problem-solving, and organizational abilities Ability to work independently and exercise sound judgment in ambiguous scenarios Passion for technological progress and AI innovation in engineering applications Requirements
PhD in Industrial or Systems Engineering with hands‑on professional experience in the field Publications or research contributions in reputable engineering journals Teaching or tutoring experience in engineering, systems optimization, or applied sciences Prior work in AI data training, technical writing, or industrial research Experience with complex, real‑world engineering systems and processes Work Environment
Based in Palo Alto, CA (in-office, 5 days per week) or fully remote with strong self‑management skills U.S.-based applicants must reside outside of Wyoming and Illinois Typical hours: 9:00am–5:30pm PST during training, then aligned with your local timezone Remote workers must use a personal computer that meets one of the following requirements: a Chromebook, a Mac running macOS 11 or newer, or a Windows PC running Windows 10 or newer Reliable smartphone access is required Compensation & Benefits
Competitive pay ranging from $90,000 to $200,000 annually for U.S.-based professionals, depending on experience and location For international candidates, compensation ranges are available upon request Access to medical benefits, subject to your country of residence Supportive, high‑impact environment focused on advancing AI and engineering innovation Application Process
Submit your resume Complete a 20-minute introductory interview Selected candidates will move on to a focused engineering data evaluation exercise Finalists will participate in a team discussion and review of their expertise The full process typically concludes within one week
#J-18808-Ljbffr