PhD in Computer Science, Linguistics, Electrical Engineering, Mathematics, Physics, or related field.
2 years leading research in sequence, speech, or audio modeling.
Experience with advanced sequence-to-sequence models and speech-text modeling techniques.
Proficient in hardware-aware model co-design and optimization using JAX, PyTorch, or TensorFlow.
One or more peer-reviewed publications in relevant machine learning or audio conferences.
Responsibilities
Define and lead research agendas and experimental designs in sequence and audio modeling.
Optimize models for efficiency and low-latency streaming inference.
Contribute to and mentor within open-source toolkits.
Benefits
Flexible working locations in Mountain View or San Francisco, CA.
15% bonus target equity.
Comprehensive benefits package including health and wellness programs.
Full Job Description
info_outline X Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; San Francisco, CA, USA.
Minimum qualifications:
PhD in Computer Science, Linguistics, Electrical Engineering, Mathematics, Physics, a related field, or equivalent practical experience.
2 years of experience leading a research agenda in sequence, speech, or audio modeling.
Experience with sequence-to-sequence models across state-space or linear attention, token-free latent representations, speech-text modeling, diffusion, flow-matching, speculative decoding, or streaming alignment.
Experience with hardware-aware model co-design, scaling laws, memory or cache optimization, or streaming inference latency in JAX, PyTorch, or TensorFlow.
One or more peer-reviewed publications in machine learning, speech, or audio conferences or journals.
Preferred qualifications:
10 years of experience in the theoretical and algorithmic aspects of sequence modeling and machine learning research.
4 years of experience setting research agendas across multiple projects or teams, and publications in NeurIPS, ICML, ICLR, JMLR, IEEE Transactions, Nature, Interspeech, ICASSP, or ACL.
Experience building, scaling, pre-training, and post-training foundational audio, speech, or multimodal models using reinforcement learning alignment or multi-resolution modeling.
Experience with model compression, distillation, or machine learning acceleration on TPUs or GPUs, and establishing evaluation benchmarks.
Contributions to open-source machine learning or speech toolkits such as JAX, PyTorch, Hugging Face Transformers, Kaldi, K2, or ESPNet.
Responsibilities
Define and lead research agendas, experimental designs, and evaluation benchmarks in sequence, speech, audio, and multimodal modeling.
Co-design and optimize models for scaling laws, memory or cache efficiency, distillation, and low-latency streaming inference in JAX, PyTorch, or TensorFlow.
Contribute to open-source toolkits, and mentor researchers.
Google is a multinational technology company that specializes in Internet-related services and products. These include online advertising technologies, search engine, cloud computing, software, and hardware. Google was founded in 1998 by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University. The company has grown tremendously since then and has become one of the most valuable companies in the world. Google's mission is to organize the world's information and make it universally accessible and useful.
