Machine Learning Applied Researcher, Speech, Vision and Audio

What you'll do

• Research and develop cutting-edge deep learning models and algorithms using vision, audio, sensor, and text modalities.
• Design and implement novel neural network architectures to solve unique challenges in Automatic Speech Recognition (ASR).
• Formulate hypotheses and run experiments to navigate ambiguous problem spaces and iterate toward solutions.
• Improve model performance while optimizing for deployment constraints like latency, memory, and compute.
• Translate research ideas into production-quality code for broad adoption across the organization.
• Identify and apply new ideas from frontier machine learning literature to current projects.

What we're looking for

• BS in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience.
• Experience in academic or industry research.
• Experience working with Pytorch.
• MS or PhD in Computer Science, Electrical Engineering, or a related field with 10+ years of relevant industry experience (preferred).
• Strong foundation in deep learning theory and hands-on experience training large-scale models (preferred).
• Deep knowledge in self-supervised learning, synthetic data generation, LLM training, or automatic speech recognition (preferred).
• Experience working with multimodal data such as images, audio, time-series, or sensor fusion (preferred).
• Publication record at top-tier ML venues such as NeurIPS, ICML, ICLR, Interspeech, or ICASSP (preferred).