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Ai Trainer Languages Jobs (NOW HIRING)

Handshake

Familiarity with tools or languages such as Python, C, or MATLAB is a plus * Strong written ... Duration: The Handshake AI program runs year-round, with projects opening periodically across ...

Handshake

Familiarity with tools or languages such as Python, C, or MATLAB is a plus * Strong written ... Duration: The Handshake AI program runs year-round, with projects opening periodically across ...

xAI

AI Tutor - Danish

Palo Alto, CA

... training and refining Grok to excel in voice interactions, speech recognition, and auditory ... Comfort providing high-quality voice recordings and feedback on audio samples in multiple languages.

xAI

AI Tutor - Bengali

Palo Alto, CA

... training and refining Grok to excel in voice interactions, speech recognition, and auditory ... Comfort providing high-quality voice recordings and feedback on audio samples in multiple languages.

xAI

AI Tutor - Hungarian

Charleston, WV

... training and refining Grok to excel in voice interactions, speech recognition, and auditory ... Comfort providing high-quality voice recordings and feedback on audio samples in multiple languages.

xAI

AI Tutor - Swahili

Charleston, WV

... training and refining Grok to excel in voice interactions, speech recognition, and auditory ... Comfort providing high-quality voice recordings and feedback on audio samples in multiple languages.

xAI

AI Tutor - Greek

Charleston, WV

... training and refining Grok to excel in voice interactions, speech recognition, and auditory ... Comfort providing high-quality voice recordings and feedback on audio samples in multiple languages.

xAI

AI Tutor - Polish

Charleston, WV

$15.75 - $20.25/hr

... training and refining Grok to excel in voice interactions, speech recognition, and auditory ... Comfort providing high-quality voice recordings and feedback on audio samples in multiple languages.

Meta

AI/HPC System Performance Engineer

Menlo Park, CA · On-site

$154K/yr

Profile and benchmark AI training and inference workloads across large-scale HPC clusters to ... Experience in developing systems software in languages like C++ * Experience with machine learning ...

xAI

AI Tutor - Portuguese

Charleston, WV

... training and refining Grok to excel in voice interactions, speech recognition, and auditory ... Comfort providing high-quality voice recordings and feedback on audio samples in multiple languages.

xAI

AI Tutor - Punjabi

Charleston, WV

... training and refining Grok to excel in voice interactions, speech recognition, and auditory ... Comfort providing high-quality voice recordings and feedback on audio samples in multiple languages.

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How much do ai trainer languages jobs pay per hour?

As of May 31, 2026, the average hourly pay for ai trainer languages in the United States is $24.74, according to ZipRecruiter salary data. Most workers in this role earn between $18.75 and $26.44 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AI Trainer Languages, and why are they important?

To thrive as an AI Trainer Languages, you need strong linguistic expertise, attention to detail, and proficiency in one or more languages, often supported by a background in linguistics or language studies. Familiarity with annotation tools, natural language processing (NLP) platforms, and data labeling systems is typically required. Excellent communication, analytical thinking, and cultural sensitivity are essential soft skills for accurately evaluating and improving AI language models. These skills ensure the quality, relevance, and inclusivity of AI-driven language technologies in diverse real-world applications.

What are some common challenges faced by AI Trainer Languages professionals when annotating or curating multilingual datasets?

AI Trainer Languages professionals often encounter challenges such as ensuring linguistic accuracy across dialects, maintaining consistency in annotation standards, and handling ambiguous or culturally nuanced language data. Coordinating with native speakers and subject matter experts is crucial to validate the quality of language data. Additionally, balancing speed and quality while meeting project deadlines can be demanding, making strong communication and attention to detail vital for success in this role.

What are AI Trainer Languages?

AI Trainer Languages are professionals who help train artificial intelligence (AI) systems by providing, evaluating, and refining language data. They work with machine learning models to improve their understanding and generation of human language, often focusing on tasks such as annotation, data labeling, and linguistic quality assurance. These trainers play a critical role in ensuring that AI systems can communicate accurately and effectively in multiple languages, adapting models for nuances, grammar, and cultural context. Their work supports the development of natural language processing (NLP) applications like chatbots, translation tools, and virtual assistants.

What is the difference between Ai Trainer Languages vs Data Annotator?

AspectAi Trainer LanguagesData Annotator
Required CredentialsBasic technical skills, sometimes certifications in AI or machine learningAttention to detail, sometimes basic technical knowledge
Work EnvironmentRemote or office-based, collaborative with AI teamsRemote or on-site, focused on labeling data
Industry UsageAI development, machine learning projectsData preparation for AI, machine learning, and analytics

Ai Trainer Languages and Data Annotator roles often overlap in data handling and technical skills. However, Ai Trainer Languages focuses more on training AI models with language data, requiring some technical knowledge of AI tools. Data Annotators primarily label and prepare data, emphasizing accuracy and attention to detail. Both roles are essential in AI development but serve different functions within the data pipeline.

AI Trainer: Code Generation

Embedding VC

Palo Alto, CA • On-site

Full-time

Posted 3 days ago

Job description

AI Trainer: Code Generation
Overview
We are building a focused group of engineers to improve how large language models reason through real world code. This initiative centers on evaluating and refining multi step reasoning trajectories derived from real GitHub repositories, with the goal of producing higher quality, more reliable code generation outputs.
This is a long term project requiring strong engineering judgment rather than surface level labeling. Contributors will work directly with complex code paths and reasoning flows across multiple platforms.
What You Will Do
You will analyze and refine multi step code reasoning trajectories generated from real production repositories.
This includes:
  • Reviewing model generated reasoning sequences
  • Identifying logical inconsistencies or weak reasoning steps
  • Improving trajectory structure to produce stronger, production grade outputs
  • Evaluating reasoning quality across different programming environments

The work is closer to debugging model logic and reasoning systems than to traditional annotation tasks.
What We Are Looking For
We are looking for engineers with strong hands on development experience and deep familiarity with real codebases.
You should:
  • Be proficient in at least two mainstream programming languages such as Python, C++, Java, TypeScript, or JavaScript
  • Have real world development experience in areas such as backend systems, frontend applications, algorithms, testing, or infrastructure
  • Be comfortable reading and reasoning through large GitHub repositories
  • Have strong written communication skills

Experience contributing to high visibility or high star GitHub repositories is a strong plus.
Additional Details
We expect to onboard approximately 10 to 20 engineers for this long term initiative. A short qualification exercise may be required prior to joining.

Apply