Remote
Full Time
● Design and fine-tune open source and proprietary LLMs for various tasks such as answering questions, summarization, reasoning and planning, etc.
● Build advanced Retrieval Augmented Generation (RAG) pipeline including rewriting, embedding fine-tuning, hybrid search, reranking, knowledge graphs, etc.
● Implement a comprehensive evaluation framework and metrics for model performance Deploy models into production environments and ensure low latency, reliability, and scalability.
● Collaborate with product team and software engineering team to build end-to-end product systems.
● Ph.D./Masters/Bachelor's degree in computer science, mathematics, statistics, engineering, or relevant field.
● Experienced in the field of NLP/LLM and well-versed with the current and latest state-of-the art research.
● Hands-on experience in various LLM fine-tuning techniques (e.g. LORA), LLM inference frameworks (e.g. vLLM), advanced RAG pipelines.
● Excellent knowledge of LLM evaluation methods and metrics.
● 6-8+ years of machine learning/deep learning experience within frameworks such as TensorFlow and/or PyTorch.
● 2+ years of practical experience in the development of generative AI application
s. ● Experience using LLMs to translate different languages. ● Publications at reputable machine learning conference or journal.
● Proficient in Python and SQL.
● Analytical and problem-solving skills.
● Ability to visualize data in the most effective way possible for a given project or study.
● Thrives in a highly demanding, entrepreneurial, and fast-paced environment.
● Is a top performer and has a proactive, "doer", and problem-solver mentality.
● Is highly flexible, has a good tolerance for ambiguity, and can quickly adapt to changing priorities.
● Is an exceptional team player with solid communication skills.
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