- Education: Master's or PhD Preferred
- 6–12+ years in Data Science / ML Engineering, with deep experience in LLM‑based systems.
Proven experience building multi-agent architectures (planner‑executor, tool‑use agents, ReAct‑style reasoning).
Strong background in RAG, embeddings, retrieval optimization, and evaluation.
Expertise in NLP, transformers, deep learning, and model fine‑tuning.
Proficiency with PyTorch, HuggingFace, LangChain/LlamaIndex, RAG, Kubernetes, and vector databases.
Experience designing production‑grade ML systems with monitoring, evaluation, and observability.
Description
This role leads the design and development of an advanced multi‑agent AI platform that powers intelligent research, drafting, and reasoning capabilities for large‑scale enterprise knowledge environments. You will architect agent frameworks, optimize retrieval‑augmented generation pipelines, fine‑tune language models, and build the infrastructure that enables AI systems to c...