As a Research Engineer at Muse, you will be responsible for building AI systems that revolutionize how music is made. We are looking for an LLM whisperer with the engineering skills needed to deploy and maintain robust inference pipelines in production, and the determination to wrangle novel music production datasets.
We believe many of the most impactful and unprecented applications of AI will be achieved by stretching, twisting, and tuning foundation models to solve wildly different use cases, and this framework requires engineers with a deep intuition for LLM behavior and willingness to experiment on the inference layer.
Requirements:
Genuinely love keeping up to date with the latest AI research
Recognize that data wrangling is critical to building state of the art AI systems, and are willing to get your hands dirty
Highly self-sufficient and comfortable making decisions under ambiguity
Have big ideas about the future of art and technology
Nice to have:
Deep understanding of how music is actually made
Experience building RAG-based agentic AI pipelines
Experience finetuning LLMs and (audio) diffusion models
Able to mentor others and grow into a leadership position
Employment type
Full-time
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