Computer Science PhD (Germany)
Anyone AI
The role
Job description
Overview
We are looking for experienced Machine Learning and AI Experts to help train and evaluate advanced AI models.
In this role, you will apply your domain expertise to assess AI-generated content, create high-quality technical prompts and answers, and evaluate model responses for accuracy, relevance, and clarity.
This is a remote, flexible opportunity for experts who want to contribute to the development of better AI systems.
Compensation
US$150 per hour
Key Responsibilities
As a Machine Learning / AI Expert, you may contribute by:
Assessing the factual accuracy, technical quality, and relevance of AI-generated text related to Machine Learning and Artificial Intelligence.
Crafting and answering advanced questions across Machine Learning, AI, and adjacent technical domains.
Evaluating, comparing, and ranking AI-generated responses based on correctness, reasoning quality, completeness, and clarity.
Identifying errors, inconsistencies, hallucinations, or weak reasoning in model outputs.
Providing clear feedback that helps improve the performance of AI systems.
Ideal Qualifications
We are especially interested in candidates with one or more of the following:
A PhD in Machine Learning, Artificial Intelligence, or an adjacent field, such as Computer Science, Statistics, Applied Mathematics, Computational Neuroscience, Natural Language Processing, Computer Vision, Reinforcement Learning, or Data Science.
Experience working as a Machine Learning Engineer, AI Researcher, Applied Scientist, Data Scientist, or in a comparable highly technical or analytical role.
Strong understanding of core Machine Learning and AI concepts, including model training, evaluation, optimization, and real-world application.
Ability to write clearly, precisely, and fluently in English about complex technical topics.
Strong analytical judgment and attention to detail.
Work Arrangement
Remote
Flexible hours
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Listing details
- Listed location
- Germany
- Annual salary
- $312,000 / year
- Employment
- PartTime
- Published
- Jun 4, 2026
- Annualized using hour × 2080.
Listing trust
- Observed through
- Ashby
- Listing last observed
- Jul 26, 2026
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