LLM Engineer

Liger Trading is a proprietary trading firm focused on high-frequency and algorithmic trading across global markets. The company combines deep market expertise with advanced technology to identify and execute opportunities in highly competitive environments. They are expanding AI capabilities by building a dedicated LLM stack to support research, automation, and internal tooling.

• Strong Python and solid ML/DL fundamentals
• Experience with PyTorch and Hugging Face ecosystem
• Hands-on experience with LLM fine-tuning (e.g. LoRA, PEFT)
• Experience training, evaluating, and comparing models
• Understanding of GPU and distributed training (e.g. DeepSpeed)
• Experience with RAG, vector databases, and retrieval systems
• Familiarity with frameworks like LangChain or LlamaIndex
• Experience with agentic workflows and emerging patterns (e.g. MCP)
• Experience deploying models using tools like vLLM, Ollama, or llama.cpp
• Proficiency in API development, Docker, and reproducible ML setups

Nice to have:

• Experience working with large-scale or low-latency systems
• Background in trading, finance, or data-intensive environments
• Interest in applying LLMs to real-time decision systems

• Develop and fine-tune LLMs for internal use cases
• Build and optimize retrieval-augmented generation (RAG) systems
• Evaluate model performance and run systematic comparisons
• Design and implement scalable inference pipelines
• Work with vector databases and retrieval/re-ranking strategies
• Deploy and maintain LLM services in production environments
• Collaborate with engineering and research teams on AI-driven tools