LLM Engineer

O projekcie: About Liger Trading Liger Trading is a proprietary trading firm focused on high-frequency and algorithmic trading across global markets. We combine deep market expertise with advanced technology to identify and execute opportunities in highly competitive environments. As we continue to expand our AI capabilities, we are building a dedicated LLM stack to support research, automation, and internal tooling. The Role We are looking for an LLM Engineer to design, build, and optimize large language model systems across the firm. This role sits at the intersection of machine learning, software engineering, and applied AI. You will work closely with researchers, engineers, and traders to deploy and scale LLM-powered solutions in real-world environments. Key Responsibilities - 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 Requirements - 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 Why Join Us - Work on high-impact AI systems used in production- Help shape how LLMs are applied in a trading environment- Collaborate with a highly technical, open-minded team- Opportunity to define and own a key area of AI development If you're interested in building practical, high-performance LLM systems - we’d like to hear from you. Wymagania: Normal 0 false false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:8.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Aptos",sans-serif; mso-ascii-font-family:Aptos; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Aptos; mso-hansi-theme-font:minor-latin; mso-font-kerning:1.0pt; mso-ligatures:standardcontextual;} Requirements - 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 Codzienne zadania: - Key Responsibilities Develop and fine-tune LLM's 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