Expertise: language_evaluation

Remote contract for native Cantonese speakers: assess Cantonese text and speech data for linguistic accuracy and fluency in internal evaluation tasks that improve language technology. No prior AI experience is required.

Evaluate and compare the quality of responses from multiple AI chatbots across real-world small business use cases. Main tasks listed: Create realistic business-related prompts based on defined user goals; Interact with multiple AI chatbots (max. 5 turns per conversation); Assess response quality across clarity, usefulness, and accuracy; Provide structured feedback and comparative evaluations.

Evaluate and compare the quality of responses from multiple AI chatbots across real-world small business use cases. Main tasks listed: Create realistic business-related prompts based on defined user goals; Interact with multiple AI chatbots (max. 5 turns per conversation); Assess response quality across clarity, usefulness, and accuracy; Provide structured feedback and comparative evaluations.

Evaluate and compare the quality of responses from multiple AI chatbots across real-world small business use cases. Main tasks listed: Create realistic business-related prompts based on defined user goals; Talents must have business-related documents available in Spanish; Interact with multiple AI chatbots (max. 5 turns per conversation); Assess response quality across clarity, usefulness, and accuracy.

We are looking for candidates with strong analytical and comprehension skills. The ideal candidate should have the ability to read, summarize, and break down large content into smaller logical blocks, conduct research online, validate claims made in the content through online research, and work with the LLM (Large Language Models) to solve puzzles! Your role is critical in helping fine-tune and improve large language models (like gpt), and will make you an expert on how to leverage AI to be a better analyst. Main tasks listed: You would spend time answering a variety of interesting analytical questions and creating scenarios that can train the LLM models to get better. Here are a couple of examples which models might get wrong and you would have to give the correct answer and explanation to enable the models to learn:; Based on a given distribution of sales by month across locations, could you analyze which location has grown the most? (Hint: what time period should we look at? should we account for sudden variability at the beginning?); In a small town, there are four distinct neighborhoods: Oak, Pine, Maple, and Elm. A postman is assigned to deliver mail and can only deliver to two neighborhoods in one day, with certain rules (e.g. Oak is always visited before Pine). If he delivers to Oak and Elm on the first day, which neighborhoods does the carrier deliver to on the second day?; Note: No other prior specialized domain experience is needed.

We are looking for candidates with strong analytical and English comprehension skills. The ideal candidate should have the ability to read, summarize, and break down large content into smaller logical blocks, conduct research online, validate claims made in the content through online research, and work with the LLM (Large Language Models) to solve puzzles! Your role is critical in helping fine-tune and improve large language models (like gpt), and will make you an expert on how to leverage AI to be a better… Main tasks listed: You would spend time answering a variety of interesting analytical questions and creating scenarios that can train the LLM models to get better. Here are a couple of examples which models might get wrong and you would have to give the correct answer and explanation to enable the models to learn:; Based on a given distribution of sales by month across locations, could you analyze which location has grown the most? (Hint: what time period should we look at? should we account for sudden variability at the beginning?); In a small town, there are four distinct neighborhoods: Oak, Pine, Maple, and Elm. A postman is assigned to deliver mail and can only deliver to two neighborhoods in one day, with certain rules (e.g. Oak is always visited before Pine). If he delivers to Oak and Elm on the first day, which neighborhoods does the carrier deliver to on the second day?; Note: No other prior specialized domain experience is needed.

We are looking for candidates with strong analytical and English comprehension skills. The ideal candidate should have the ability to read, summarize, and break down large content into smaller logical blocks, conduct research online, validate claims made in the content through online research, and work with the LLM (Large Language Models) to solve puzzles! Your role is critical in helping fine-tune and improve large language models (like gpt), and will make you an expert on how to leverage AI to be a better… Main tasks listed: You would spend time answering a variety of interesting analytical questions and creating scenarios that can train the LLM models to get better. Here are a couple of examples which models might get wrong and you would have to give the correct answer and explanation to enable the models to learn:; Based on a given distribution of sales by month across locations, could you analyze which location has grown the most? (Hint: what time period should we look at? should we account for sudden variability at the beginning?); In a small town, there are four distinct neighborhoods: Oak, Pine, Maple, and Elm. A postman is assigned to deliver mail and can only deliver to two neighborhoods in one day, with certain rules (e.g. Oak is always visited before Pine). If he delivers to Oak and Elm on the first day, which neighborhoods does the carrier deliver to on the second day?; Note: No other prior specialized domain experience is needed.

We are looking for candidates with strong analytical and English comprehension skills. The ideal candidate should have the ability to read, summarize, and break down large content into smaller logical blocks, conduct research online, validate claims made in the content through online research, and work with the LLM (Large Language Models) to solve puzzles! Your role is critical in helping fine-tune and improve large language models (like gpt), and will make you an expert on how to leverage AI to be a better… Main tasks listed: You would spend time answering a variety of interesting analytical questions and creating scenarios that can train the LLM models to get better. Here are a couple of examples which models might get wrong and you would have to give the correct answer and explanation to enable the models to learn:; Based on a given distribution of sales by month across locations, could you analyze which location has grown the most? (Hint: what time period should we look at? should we account for sudden variability at the beginning?); In a small town, there are four distinct neighborhoods: Oak, Pine, Maple, and Elm. A postman is assigned to deliver mail and can only deliver to two neighborhoods in one day, with certain rules (e.g. Oak is always visited before Pine). If he delivers to Oak and Elm on the first day, which neighborhoods does the carrier deliver to on the second day?; Note: No other prior specialized domain experience is needed.

We are looking for candidates with strong analytical and English comprehension skills. The ideal candidate should have the ability to read, summarize, and break down large content into smaller logical blocks, conduct research online, validate claims made in the content through online research, and work with the LLM (Large Language Models) to solve puzzles! Your role is critical in helping fine-tune and improve large language models (like gpt), and will make you an expert on how to leverage AI to be a better… Main tasks listed: You would spend time answering a variety of interesting analytical questions and creating scenarios that can train the LLM models to get better. Here are a couple of examples which models might get wrong and you would have to give the correct answer and explanation to enable the models to learn:; Based on a given distribution of sales by month across locations, could you analyze which location has grown the most? (Hint: what time period should we look at? should we account for sudden variability at the beginning?); In a small town, there are four distinct neighborhoods: Oak, Pine, Maple, and Elm. A postman is assigned to deliver mail and can only deliver to two neighborhoods in one day, with certain rules (e.g. Oak is always visited before Pine). If he delivers to Oak and Elm on the first day, which neighborhoods does the carrier deliver to on the second day?; Note: No other prior specialized domain experience is needed.

We are looking for candidates with strong analytical and English comprehension skills. The ideal candidate should have the ability to read, summarize, and break down large content into smaller logical blocks, conduct research online, validate claims made in the content through online research, and work with the LLM (Large Language Models) to solve puzzles! Your role is critical in helping fine-tune and improve large language models (like gpt), and will make you an expert on how to leverage AI to be a better… Main tasks listed: You would spend time answering a variety of interesting analytical questions and creating scenarios that can train the LLM models to get better. Here are a couple of examples which models might get wrong and you would have to give the correct answer and explanation to enable the models to learn:; Based on a given distribution of sales by month across locations, could you analyze which location has grown the most? (Hint: what time period should we look at? should we account for sudden variability at the beginning?); In a small town, there are four distinct neighborhoods: Oak, Pine, Maple, and Elm. A postman is assigned to deliver mail and can only deliver to two neighborhoods in one day, with certain rules (e.g. Oak is always visited before Pine). If he delivers to Oak and Elm on the first day, which neighborhoods does the carrier deliver to on the second day?; Note: No other prior specialized domain experience is needed.