"audio ml" Jobs
31 open tech roles matching “audio ml”, taken straight from company career pages — not reposted from other job boards. Most in demand right now: Python, AI/ML, PyTorch. Every listing is re-checked daily and closed roles are removed.
Showing 20 of 31 results
Join Together AI as a Staff ML Engineer to optimize voice model serving for real-time applications on a high-impact team.
Join Decagon as a Research Engineer to build next-generation AI voice agents in a collaborative, onsite environment.
Lead research in audio-visual avatar generation at Tavus, shaping the future of human-AI interaction.
Join Cartesia as a Research Engineer to design high-quality datasets and engineer data pipelines for cutting-edge AI models.
Join Tavus as a Conversational Modelling Research Engineer to advance AI Humans through innovative multimodal conversational models.
Join HappyRobot as a Machine Learning Engineer to build AI models for human-like conversations and shape the future of AI infrastructure.
Lead the development of next-generation multimodal models at Twelve Labs, impacting thousands of customers worldwide.
Join Sesame as a Staff Software Engineer to lead the development of backend infrastructure for innovative voice agent technology.
Join Cartesia as a Software Engineer to shape data infrastructure for cutting-edge AI models in a collaborative, in-office environment.
Drive technical direction for training infrastructure and operations within Pegasus at a growing AI company focused on video understanding.
Lead the development of models and algorithms for Decagon's real-time voice agents in a collaborative, onsite environment.
Drive research on Pegasus's complex problems in a hybrid role at a growing AI company focused on video understanding.
Join Inferact as an inference runtime engineer to optimize AI model execution across diverse hardware and architectures.
Join Sesame as a Backend Software Engineer to tackle complex challenges in building reliable, scalable systems for innovative voice agents.
Build and operate production ML systems for Pegasus, focusing on reliability and performance in a hybrid work environment.