LLM Engineer

Role Summary [компания] is looking for an LLM Engineer to design, fine-tune, and deploy large language model solutions that solve real business problems. You'll work across the model lifecycle — from prompt and architecture design to evaluation and production monitoring — collaborating with product and engineering teams to ship reliable AI features. Key Responsibilities - Design, fine-tune, and optimize large language models for specific use cases - Build and maintain evaluation harnesses to measure model quality and safety - Implement RAG (retrieval-augmented generation) pipelines and prompt strategies - Monitor model performance in production and iterate on improvements - Collaborate with product and engineering teams to integrate LLM features - Stay current with emerging LLM research, architectures, and tooling Requirements Requirements - 3+ years of hands-on experience with large language models and NLP - Strong understanding of transformer architectures (GPT, BERT, LLaMA, etc.) - Proficiency in Python and ML frameworks such as PyTorch or TensorFlow - Experience with fine-tuning, prompt engineering, and hyperparameter optimization - Track record of deploying ML/LLM systems in production environments Nice-to-Haves - Experience with vector databases and RAG pipelines - Familiarity with model quantization and inference optimization - Background in AI safety or content moderation systems Highlights Build and deploy cutting-edge LLM solutions using AI, RAG, and modern ML frameworks. Originally posted on Himalayas