LLM Engineer

This is your mission

• Model Development & Fine-Tuning: Design, train, fine-tune, and evaluate large language models (LLMs) using domain-specific or proprietary data to meet business needs.
• Prompt Engineering: Craft, test, and optimize prompts to improve model outputs.
• LLM Integration: Deploy and integrate LLMs into production applications, including agentic solutions, RAG, chatbots, designing APIs, latency/throughput optimization, and monitoring.
• Research & Experimentation: Stay current with state-of-the-art LLM architectures and techniques, and evaluate their application for internal use cases.
• Stakeholder Collaboration: Collaborate with product, data, and engineering teams to translate business problems into LLM-powered solutions and communicate model limitations or trade-offs effectively.

What you bring along

• Minimum 3 years of hands-on experience with LLMs, NLP, or foundation model development in an industry setting.
• Deep understanding of transformer-based models and modern NLP techniques.
• Proficiency in Python and experience with common LLM/NLP libraries and frameworkS.
• Experience with fine-tuning and serving LLMs.
• Familiarity with vector databases and retrieval-augmented generation (RAG) pipelines.
• Experience with MLOps, cloud infrastructure (AWS/GCP/Azure), and model deployment tools for LLM-based systems.

Your benefits