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описание
The client is a foundational LLM company focused on enhancing large language models through proprietary data for fine-tuning and benchmarking model performance.
задачи
Design, develop, and maintain efficient, high-quality Python code to train and optimize AI models;
Conduct evaluations to benchmark model performance and analyze results for continuous improvement;
Evaluate and rank AI model responses to user queries across diverse domains against predefined criteria;
Lead supervised fine-tuning efforts, including creating and maintaining high-quality, task-specific datasets;
Collaborate with researchers and annotators to execute reinforcement learning with human feedback and refine reward models.
требования
Proficiency in Python and related frameworks and libraries for AI/ML tasks;
Experience with supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF);
Strong understanding of evaluation strategies and benchmarking processes for AI models;
Ability to design and implement Python code for data generation and model optimization;
Familiarity with AI model response evaluation and ranking methodologies.