LLM Engineer

Stack

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

• ▹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 have

• ▹Experience with vector databases and RAG pipelines
• ▹Familiarity with model quantization and inference optimization
• ▹Background in AI safety or content moderation systems

Soft skills