About the job
Job Summary:
- Take the lead in developing comprehensive solutions utilizing Large Language Models (LLMs).
- Foster innovation and apply LLMs to address intricate business challenges effectively.
- Engage in cross-functional collaboration to create scalable and value-oriented LLM systems.
Key Responsibilities:
- LLM-Centric Solution Development:
- Architect, refine, and deploy state-of-the-art LLMs for applications such as content generation, intelligent assistants, semantic search, and knowledge retrieval.
- Assess and select suitable foundational models (e.g., GPT, LLaMA, Mistral) and customize them for specific organizational needs.
- Develop modular and scalable pipelines for LLM applications, encompassing prompt engineering, inference optimization, and feedback mechanisms.
- Collaborative Project Contribution:
- Partner with Machine Learning Engineers, Data Engineers, DevOps Engineers, Developers, and stakeholders to establish project objectives and align model functionalities with business goals.
- Translate high-level requirements into actionable development strategies with clear KPIs.
- Support the end-to-end lifecycle of LLM projects from initial experimentation through to deployment.
- Technical Excellence:
- Remain abreast of the rapidly evolving landscape of LLMs, including open-source models, toolkits (e.g., Hugging Face, LangChain), and retrieval-augmented generation (RAG) frameworks.
- Optimize the cost, performance, and latency of LLM inference at scale.
- Ensure reproducibility, quality, and efficiency throughout LLM workflows.
- Effective Communication & Collaboration:
- Clearly articulate technical findings and solution designs to diverse audiences, both technical and non-technical.
- Contribute to internal LLM best practices and knowledge sharing.
- Provide technical support and informal mentoring regarding LLM topics across teams.
