About Turing
Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems.
Turing helps customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies.
Role Overview
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.
For example, for SFT data generation, you might have to put together or be provided a prompt which contains provided code and questions, you will then provide the model responses, and write corresponding Python code to solve the questions.
For RLHF data generation, you may need to create a prompt yourself or use one provided by the customer, ask the model questions, and evaluate the outputs generated by two versions of the LLM. You'll compare these outputs and provide feedback, which is then used to fine-tune the models. Please note that this role does not involve building or fine-tuning LLMs.
What does day-to-day look like
- 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.