Machine Learning Researcher, Multimodal LLMs

Experience with LLMs, multimodal models, or speech-language systems

Deep understanding of prompting, fine-tuning, and alignment techniques

Familiarity with neural audio codecs and modern multimodal LLM techniques

You can go from idea → dataset → experiment → conclusion in days

You know how to design experiments that actually answer the question

Strong sense for what makes an interaction feel natural vs robotic

Ability to translate abstract modeling ideas into user-facing improvements

You take ownership from research through deployment

You thrive in ambiguous, fast-moving environments

You care about impact, not just elegance

You think in systems, not just models

You obsess over latency, correctness, and real-world behavior

You are comfortable discarding ideas quickly when data disagrees

You push toward simple abstractions for complex problems

Experience with real-time voice systems or conversational AI

Background in tool-using agents or agent frameworks

Experience with multimodal datasets (audio + text + actions)

Contributions to LLM or speech-related research or open source