Job Summary : xAI is a company focused on creating AI systems that enhance human understanding and knowledge. They are seeking an AI Tutor specialized in multilingual audio capabilities to train and ...
Job Summary : xAI is a company focused on creating AI systems that enhance human understanding and knowledge. They are seeking an AI Tutor specialized in multilingual audio capabilities to train and ...
Job Summary : xAI is focused on creating AI systems that enhance human understanding and knowledge. They are seeking an AI Tutor specialized in multilingual audio capabilities to train and refine ...
Job Summary : xAI is focused on creating AI systems that enhance human understanding and knowledge. They are seeking an AI Tutor specialized in multilingual audio capabilities to train and refine ...
Xai Tutor information
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$8.17 - $10.38
5% of jobs
$10.38 - $12.59
6% of jobs
$14.43 is the 25th percentile. Wages below this are outliers.
$12.59 - $14.79
16% of jobs
$14.79 - $17
15% of jobs
The median wage is $17.97 / hr.
$17 - $19.21
17% of jobs
$19.21 - $21.42
11% of jobs
$21.42 - $23.62
4% of jobs
$23.78 is the 75th percentile. Wages above this are outliers.
$23.62 - $25.83
7% of jobs
$25.83 - $28.04
4% of jobs
$28.04 - $30.24
13% of jobs
$30.24 - $32.45
1% of jobs
$8
$20
$32
How much do xai tutor jobs pay per hour?
As of Jul 26, 2026, the average hourly pay for xai tutor in the United States is $20.22, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $24.04 per hour, depending on experience, location, and employer.
How do I become an AI tutor?
To become an AI tutor, you typically need a strong understanding of artificial intelligence, machine learning, and programming languages such as Python. Gaining relevant certifications, building a portfolio of projects, and experience in teaching or tutoring can also help qualify you for this role.
What is a Xai Tutor job?
A Xai Tutor is responsible for teaching and assisting users in understanding Explainable AI (XAI) concepts, models, and applications. They help bridge the gap between complex AI decisions and human comprehension by providing clear explanations and guidance. This role may involve creating educational materials, answering user queries, and facilitating discussions on AI transparency and interpretability. Xai Tutors often work with students, professionals, or organizations looking to enhance their understanding of AI models and their decision-making processes.
How much do xAI model behavior tutors make?
Salaries for xAI model behavior tutors vary depending on experience, location, and employer, but typically range from $15 to $30 per hour. These roles often require knowledge of AI concepts and strong communication skills, with some positions offering part-time or flexible schedules.
What does an xAI tutor do?
An xAI tutor helps students or professionals understand explainable artificial intelligence concepts and tools. They may provide instruction on AI models, interpretability techniques, and related software, often working in educational or training environments to improve understanding of AI transparency and accountability.
What are some common challenges XAI Tutors face, and how can they be addressed?
XAI Tutors often encounter learners with varying levels of technical background, which can make it challenging to present explainability concepts clearly and effectively. Managing evolving AI technologies and staying up-to-date with new research also requires continuous learning and adaptability. To address these challenges, XAI Tutors frequently personalize their teaching approach, utilize interactive examples, and engage in professional development. Collaborating with faculty, other tutors, or technical teams can further enrich the learning experience and ensure material remains relevant and accessible.
How much do AI tutors get paid?
AI tutors, including those teaching or developing AI-based educational tools, typically earn between $15 and $40 per hour depending on experience, location, and the platform. Freelance or remote AI tutoring roles may offer higher rates for specialized skills in AI, machine learning, or programming.
What are the key skills and qualifications needed to thrive in the Xai Tutor position, and why are they important?
To thrive as an XAI Tutor, you need a solid understanding of explainable artificial intelligence concepts, machine learning fundamentals, and instructional design, often backed by a degree in computer science or a related field. Familiarity with platforms like TensorFlow, PyTorch, and educational tools such as LMS (Learning Management Systems) or interactive coding environments is typically expected. Strong communication skills, patience, and the ability to tailor complex concepts for diverse learners are vital soft skills for success. These skills and qualities ensure effective knowledge transfer, foster learner engagement, and support the practical application of XAI principles in real-world scenarios.
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Full-time
Posted 10 days ago
Job description
Job Summary:
xAI is a company focused on creating AI systems that enhance human understanding and knowledge. They are seeking an AI Tutor specialized in multilingual audio capabilities to train and refine AI systems for voice interactions and speech recognition across diverse languages and cultural contexts.
Responsibilities:
• Use proprietary software to provide labels, annotations, recordings, and inputs on projects involving multilingual audio clips, voice recordings, speech samples, and auditory elements in various languages.
• Support the delivery of high-quality curated audio data that ensures clear, natural spoken output, accurate representation of linguistic and prosodic details (such as intonation, rhythm, and accent), and professional audio standards.
• Collaborate with technical staff to develop tasks that improve AI's ability to handle speech modulation, accent variation, noise in real-world recordings, and multilingual audio processing.
• Work with technical staff to improve annotation tools for efficient audio workflows.
Qualifications:
Required:
• Native proficiency in Chinese with exposure to diverse accents, dialects, or regional variations.
• Proficiency in English (minimum B2 level) with clear, natural vocal delivery and pronunciation suitable for audio recording purposes.
• Strong auditory perception to identify nuances in speech, accents, pronunciation, intonation, and audio quality across languages.
• Demonstrated ability to handle multilingual audio content, including evaluating speech accuracy, cultural vocal expressions, and contextual interpretation in spoken form.
• Demonstrated ability to transcribe audio with high accuracy across accents and varying audio quality.
• Comfort providing high-quality voice recordings and feedback on audio samples in multiple languages.
• Strong comprehension skills and the ability to make independent judgments on ambiguous or varied audio material, including noisy or accented speech.
• Strong communication, interpersonal, analytical, detail-oriented, and organizational skills, with the ability to articulate audio-related feedback effectively.
• Commitment to developing AI that masters sophisticated multilingual audio capabilities.
Preferred:
• Demonstration of exceptional attention to linguistic nuance, auditory detail, and data quality beyond standard transcription work.
• Deep understanding and taste of what good/useful Audio data is.
• Strong command of advanced transcription and annotation practices, including handling disfluencies, accents, and prosodic features (intonation, stress, rhythm, emotion, etc) with high consistency and accuracy.
• Background in linguistics (e.g., phonetics, phonology, sociolinguistics), speech sciences, cognitive science, or a related field, or equivalent practical experience, with demonstrated ability to analyze accent variation, pronunciation differences, and multilingual speech patterns.
• Experience working with speech/audio datasets, annotation workflows, or AI training data, including knowledge/experience with training voice models, and an understanding of how data quality impacts model performance.
• Professional experience in voice work, including voice acting, voice recording, podcasting with a measurable audience (e.g., X following), or similar audio production demonstrating attention to clarity and recording quality.
• Demonstrated ability to exercise independent judgment in ambiguous audio scenarios and make consistent, defensible annotation decisions.
• Portfolio (strongly preferred for advanced candidates): Voice samples, annotated transcripts, or audio-related work demonstrating quality, methodology, and attention to detail.
• Candidates with professional experience in voice, linguistics, speech data, or speech evaluation and research are especially encouraged to apply.
Company:
SpaceXAI develops AI software and computational infrastructure designed for scientific discovery, automated reasoning, and data processing. It is a sub-organization of SpaceX. Founded in 2023, the company is headquartered in Palo Alto, USA, with a team of 1001-5000 employees. The company is currently Late Stage.
xAI is a company focused on creating AI systems that enhance human understanding and knowledge. They are seeking an AI Tutor specialized in multilingual audio capabilities to train and refine AI systems for voice interactions and speech recognition across diverse languages and cultural contexts.
Responsibilities:
• Use proprietary software to provide labels, annotations, recordings, and inputs on projects involving multilingual audio clips, voice recordings, speech samples, and auditory elements in various languages.
• Support the delivery of high-quality curated audio data that ensures clear, natural spoken output, accurate representation of linguistic and prosodic details (such as intonation, rhythm, and accent), and professional audio standards.
• Collaborate with technical staff to develop tasks that improve AI's ability to handle speech modulation, accent variation, noise in real-world recordings, and multilingual audio processing.
• Work with technical staff to improve annotation tools for efficient audio workflows.
Qualifications:
Required:
• Native proficiency in Chinese with exposure to diverse accents, dialects, or regional variations.
• Proficiency in English (minimum B2 level) with clear, natural vocal delivery and pronunciation suitable for audio recording purposes.
• Strong auditory perception to identify nuances in speech, accents, pronunciation, intonation, and audio quality across languages.
• Demonstrated ability to handle multilingual audio content, including evaluating speech accuracy, cultural vocal expressions, and contextual interpretation in spoken form.
• Demonstrated ability to transcribe audio with high accuracy across accents and varying audio quality.
• Comfort providing high-quality voice recordings and feedback on audio samples in multiple languages.
• Strong comprehension skills and the ability to make independent judgments on ambiguous or varied audio material, including noisy or accented speech.
• Strong communication, interpersonal, analytical, detail-oriented, and organizational skills, with the ability to articulate audio-related feedback effectively.
• Commitment to developing AI that masters sophisticated multilingual audio capabilities.
Preferred:
• Demonstration of exceptional attention to linguistic nuance, auditory detail, and data quality beyond standard transcription work.
• Deep understanding and taste of what good/useful Audio data is.
• Strong command of advanced transcription and annotation practices, including handling disfluencies, accents, and prosodic features (intonation, stress, rhythm, emotion, etc) with high consistency and accuracy.
• Background in linguistics (e.g., phonetics, phonology, sociolinguistics), speech sciences, cognitive science, or a related field, or equivalent practical experience, with demonstrated ability to analyze accent variation, pronunciation differences, and multilingual speech patterns.
• Experience working with speech/audio datasets, annotation workflows, or AI training data, including knowledge/experience with training voice models, and an understanding of how data quality impacts model performance.
• Professional experience in voice work, including voice acting, voice recording, podcasting with a measurable audience (e.g., X following), or similar audio production demonstrating attention to clarity and recording quality.
• Demonstrated ability to exercise independent judgment in ambiguous audio scenarios and make consistent, defensible annotation decisions.
• Portfolio (strongly preferred for advanced candidates): Voice samples, annotated transcripts, or audio-related work demonstrating quality, methodology, and attention to detail.
• Candidates with professional experience in voice, linguistics, speech data, or speech evaluation and research are especially encouraged to apply.
Company:
SpaceXAI develops AI software and computational infrastructure designed for scientific discovery, automated reasoning, and data processing. It is a sub-organization of SpaceX. Founded in 2023, the company is headquartered in Palo Alto, USA, with a team of 1001-5000 employees. The company is currently Late Stage.