Research Scientist Intern, Audio Quality with AI (PhD)

• Investigate systematic phonemic errors as causal factors in perceived speech quality degradation, and link them to human perceptual judgments
• Build and curate datasets and benchmarks of speech for phoneme-level analysis
• Explore and compare the capabilities of audio and video (multimodal) LLMs as tools to support this analysis
• Relate findings to human perceptual data (quality preference and intelligibility) and translate them into actionable insights for research and engineering teams
• Where appropriate, adapt multimodal models to the task in a supporting capacity
• Collaborate with researchers, engineers, and cross-functional partners to define goals, communicate findings, and drive improvements in speech quality
• Develop tools and infrastructure to streamline and scale the analysis
• Stay current with research in speech perception and audio quality and intelligibility assessment, and incorporate best practices into Meta's workflows
• Disseminate results through internal reports and presentations, and, when appropriate, external publications

• Currently has, or is in the process of obtaining, a PhD degree in the field of Speech and Hearing Science, Auditory Neuroscience, Computational Neuroscience, Computer Science, Artificial Intelligence, Generative AI, Transformer Models, Machine Learning, Signal Processing or Computer vision
• 3+ years experience with Python, Matlab, or similar
• 3+ years experience with machine learning software platforms such as PyTorch, TensorFlow, etc
• Background in speech perception, psychoacoustics, or acoustic phonetics
• Experience deploying novel audio computational models and LLMs
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

• Experience building novel audio computational models and LLMs
• Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. Github)
• Experience in advancing AI techniques, including core contributions to open source libraries and frameworks in computer vision or audio processing
• Experience with audio and speech quality assessment
• Experience with multichannel audio processing
• Experience in visual and acoustic scene analysis
• Experience manipulating and analyzing complex, large scale, high-dimensionality data from varying sources
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or top computer vision and machine learning conferences such as ARO, ASA, NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, ICCV, ECCV, ICASSP, InterSpeech or simila
• Experience in utilizing theoretical and empirical research to solve problems
• Experience working and communicating cross functionally in a team environment
• Intent to return to a degree-program after the completion of the internship/co-op

benefits