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Temporary Ai Language Trainer Jobs (NOW HIRING)

Unconventional AI

AI Systems, Training

Palo Alto, CA · On-site

$123K - $168K/yr

Unconventional AI is a company focused on redefining computing to solve the energy limitations of ... language, and world models. • Design and scale multi-node distributed training systems ...

Welo Global

Project Lyra Urdu Culture Expert

$15/hr

In this role, you will contribute to training AI systems to better understand, generate, and refine language by performing structured evaluation and writing tasks, all from the comfort of your home ...

Weekday AI

Biology Expert (PhD) - AI Trainer

$100/hr

In this role, you will help develop and evaluate advanced AI systems designed to replicate real ... Support data generation and evaluation processes to improve next-generation large language models ...

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How much do temporary ai language trainer jobs pay per hour?

As of Jul 2, 2026, the average hourly pay for temporary ai language trainer in the United States is $31.24, according to ZipRecruiter salary data. Most workers in this role earn between $19.95 and $35.58 per hour, depending on experience, location, and employer.

How does a Temporary AI Language Trainer typically collaborate with engineering and data science teams during a project?

As a Temporary AI Language Trainer, you will frequently work closely with engineering and data science teams to provide linguistic expertise and insights. This often involves reviewing datasets, annotating language data, and offering feedback on model outputs to help improve AI performance. Effective communication and a collaborative mindset are key, as you'll be expected to clarify language nuances, participate in regular project meetings, and align your work with overall project goals. This cross-functional teamwork ensures that the AI models are both technically robust and linguistically accurate.

What are Temporary AI Language Trainers?

Temporary AI Language Trainers are professionals hired on a short-term basis to help develop, train, and improve artificial intelligence language models. Their responsibilities typically include reviewing, annotating, and generating text data, assessing AI outputs for quality and accuracy, and providing feedback to enhance the model's performance. These roles are crucial for refining AI systems to better understand and generate human language, often requiring strong language skills and attention to detail. Temporary positions may be project-based or seasonal, offering flexibility for both employers and workers.

What are the key skills and qualifications needed to thrive as a Temporary AI Language Trainer, and why are they important?

To thrive as a Temporary AI Language Trainer, you need strong linguistic abilities, attention to detail, and often a background in linguistics, language studies, or a related field. Familiarity with annotation tools, content management systems, and sometimes experience with machine learning platforms or data labeling software is typically required. Excellent communication, critical thinking, and time management are standout soft skills for this role. These skills ensure high-quality training data, accurate language processing, and effective collaboration with technical teams to improve AI language models.
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Temporary Ai Language Trainer jobs near you
Infographic showing various Temporary Ai Language Trainer job openings in the United States as of June 2026, with employment types broken down into 74% Full Time, 24% Part Time, 1% Temporary, and 1% Contract. Highlights an 99% Physical, and 1% Remote job distribution, with an average salary of $64,984 per year, or $31.2 per hour.

AI Systems, Training

Unconventional AI

Palo Alto, CA • On-site

$123K - $168K/yr

Full-time

Posted 28 days ago

Job description

Job Summary:
Unconventional AI is a company focused on redefining computing to solve the energy limitations of AI. They are seeking a key contributor to build a next-generation ML model training platform and co-design training systems alongside novel AI models and hardware.
Responsibilities:
• Build and maintain highly optimized, model-specific training stacks specifically tuned for state-of-the-art generative vision, language, and world models.
• Design and scale multi-node distributed training systems, implementing elastic sharding and robust data streaming pipelines for fast, large-scale iteration. Implement and robust model checkpointing and recovery mechanisms.
• Develop and optimize kernels using low-level programming models like CUDA and Triton. Design rigorous benchmarking suites to track Model Flops Utilization (MFU), memory bandwidth, and convergence stability.
• Act as a translator, discussing algorithmic trade-offs with theorists and converting model requirements into concrete specifications for infrastructure and hardware engineering teams.
Qualifications:
Required:
• Education: An MS/PhD or equivalent research/project experience in a quantitative field such as AI/Machine Learning, Computer Science, Physics, Electrical Engineering, or Applied Math.
• Experience: Veteran of the modern ML software stack. Demonstrated ability to map state-of-the-art AI model architectures (e.g., transformers, Mixture of Experts, diffusion models) to system performance implication. Deep expertise in how models are partitioned across a cluster, with a mastery of communication primitives, and parallelism strategies.
• Software Development: Proven track record of implementing, debugging, and maintaining production-grade training frameworks—such as Megatron-LM, DeepSpeed, Ray, PyTorch Lightning—turning raw compute into a reliable model-building factory.
Preferred:
• Unconventional Co-Design: A forward-looking perspective on co-designing algorithms for unconventional computing paradigms that map closely to the physics of underlying systems.
Company:
Unconventional AI rethinks computer foundations to optimize energy efficiency for AI. Founded in 2025, the company is headquartered in San Francisco, USA, with a team of 11-50 employees. The company is currently Early Stage.

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