Applied Scientist - Deep Learning (Fully remote, U.S. Only)

Applied Scientist - Deep Learning Fully remote, U.S. Only. ‍ Incept AI is solving the last mile problem in Voice AI. Our team of PhD applied scientists and software engineers builds neural audio processing systems, audio-processing foundation models, and agentic AI workflows that make Voice AI reliable and truly useful in the real world. Our first application is the lucrative drive-thru and phone automation market for restaurants. We have built the most accurate order-taking restaurant Voice AI assistant in the world, and are working with major restaurant chains to help elevate their customer service while providing major automation-led savings. As an Applied Scientist in our early stage startup team, your job will be to build state-of-the-art audio processing deep learning models, at small and larger scales, fine-tune / post-train foundation models, build benchmarks that align with customer needs, build data pipelines, and run experiments to continually improve our systems. If you love applied deep learning, and seeing your work delighting customers at scale, if you believe that great applied science comes from great empirical work and great engineering along with great new ideas, if you would like to be part of a tight-knit team getting a example-setting win in customer obsessed AI, then you will love working at Incept. – We are a remote-first startup that values a tight collaboration and connection with each other and have created a unique fully distributed work culture based on a virtual office. This allows us to be open to candidates in all US locations, who are authorized to work in the United States. This position is not eligible for visa sponsorship. Requirements: - PhD in a technical field or equivalent applied deep learning experience. - Experience training deep learning models. Bonus: - Experience working with Pytorch. - Experience in building neural audio processing models. If interested, please send a resume to umut at incept dot ai. Apply tot his job

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