Liquid AI, San Francisco +1
On Liquid’s Applied ML team, you’ll adapt our audio models for enterprise products where a spoken request needs to trigger the right action. When someone asks a voice assistant to “turn down the passenger-side temperature,” the model needs to select the right tool, pass the right arguments, and confirm what changed, even in a noisy cabin.
You’ll work directly with customers to define what reliable behavior looks like, then own the data, post-training, evaluation, and delivery needed to achieve it. What you learn from those deployments will help improve Liquid’s audio models and post-training pipelines.
Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there.
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Source: the Liquid AI Ashby job board. We last checked this job 2 h ago. We first saw it 8 days ago. A job on a job board does not always mean that the team interviews people now. We found this job board in a public list. We did not yet compare it with the careers page of the company.
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