Mercor

Systems Engineering Tutor

Mercor Berlin

Stellenbeschreibung:

1. Role Overview

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.

You will collaborate closely with technical teams to design new AI tasks, improve annotation tools, and select challenging engineering problems that enhance model reasoning and performance. This role requires analytical precision, adaptability, and a strong interest in technology-driven innovation.

2. Key Responsibilities

  • Use proprietary tools to label, annotate, and evaluate data across industrial and systems engineering domains
  • Support AI training initiatives by curating high-quality, structured datasets
  • Collaborate with research teams to refine annotation processes and enhance workflow efficiency
  • Analyze complex engineering problems and assess AI-generated solutions for technical accuracy
  • Interpret evolving task instructions with precision, applying strong professional judgment

3. Ideal 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

4. Preferred Background

  • 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

5. 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

6. 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

7. 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

8. About Mercor

Mercor is based in San Francisco, CA and specializes in recruiting experts for top AI labs. Our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

NOTE / HINWEIS:
EnglishEN: Please refer to Fuchsjobs for the source of your application
DeutschDE: Bitte erwähne Fuchsjobs, als Quelle Deiner Bewerbung

Stelleninformationen

  • Veröffentlichungsdatum:

    29 Nov 2025
  • Standort:

    Berlin
  • Typ:

    Vollzeit
  • Arbeitsmodell:

    Vor Ort
  • Kategorie:

  • Erfahrung:

    2+ years
  • Arbeitsverhältnis:

    Angestellt

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