Applied Scientist - Deep Learning

Role overview Develop deep learning systems that improve the reliability of voice AI in live, demanding environments. The work covers audio-processing models, foundation-model adaptation, evaluation benchmarks, data pipelines, and experiments, combining applied research with strong engineering and a direct connection to customer outcomes. The position is fully remote within the United States and is not eligible for visa sponsorship.

Responsibilities - Train audio-processing deep learning models at different scales. - Fine-tune and post-train foundation models for voice applications. - Create benchmarks that reflect real customer and product requirements. - Build data pipelines supporting model development and evaluation. - Run experiments and use empirical results to improve system performance. - Collaborate on applied science and engineering for production voice AI.

Requirements - PhD in a technical field or equivalent applied deep learning experience. - Experience training deep learning models. - Strong applied research and experimental problem-solving skills.

Nice to have - Experience working with PyTorch. - Background building neural audio-processing models.

Benefits and work setup - Fully remote role for candidates located in the United States. - Distributed, collaboration-oriented work environment. - Visa sponsorship is unavailable; candidates must be authorized to work in the United States.