Language: English

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.

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.

This position is within a project with one of the foundational LLM companies. The goal is to assist these foundational LLM companies in enhancing their Large Language Models. One way we help these companies improve their models is by providing them with high-quality proprietary data. This data serves two main purposes: first, as a basis for fine-tuning their models, and second, as an evaluation set to benchmark the performance of their models or competitor models. Main tasks listed: Design, develop, and maintain efficient, high-quality Python code to train and optimize AI models; Conduct evaluations (Evals) to benchmark model performance and analyze results for continuous improvement; Familiarity with Python frameworks and libraries; Evaluate and rank AI model responses to user queries across diverse domains, ensuring alignment with predefined criteria.

We are actively seeking talented Data Scientists & Analysts proficient in Python to join our ambitious team dedicated to pushing the frontiers of AI technology. This opportunity is tailored for professionals who thrive on developing innovative solutions and aspire to be at the forefront of AI advancements. You will work with companies in the US looking to develop cutting-edge commercial and research AI solutions. Main tasks listed: Design, develop, and maintain efficient, high-quality code to train and optimize AI models; Conduct evaluations (Evals) to benchmark model performance and analyze results for continuous improvement; Evaluate and rank AI model responses to user queries across diverse domains, ensuring alignment with predefined criteria; Develop comprehensive explanations and rationales for evaluations, showcasing excellent reasoning and technical expertise.