Research Software Engineer, Google Research

• Design, implement, and rigorously test novel modeling and algorithmic improvements for foundational audio models.
• Solve complex, open-ended challenges in audio understanding architectures, sequence modeling, and fast inference.
• Write product or system development code to integrate and evaluate audio capabilities across the ecosystem.
• Participate in or lead design reviews with peers and stakeholders to decide amongst available technologies.
• Triage product or system issues and debug, track, and resolve them by analyzing the sources of issues and their impact on service operations and quality.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
• Experience in machine learning research, or quantitative research in fields such as mathematics, physical sciences, engineering, or economics.
• Experience with machine learning frameworks (e.g., JAX or PyTorch).

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical fields.
• Publication in journals or conferences in machine learning or quantitative fields such as mathematics, physical sciences, engineering, or economics.
• Experience with sequence modeling, machine translation, speech/audio processing, diffusion language models, or reinforcement learning.
• Experience in building, scaling, and optimizing complex machine learning systems.
• Contribution to major open-source projects related to machine learning such as JAX, PyTorch, HuggingFace Transformers, Kaldi K2, ESPNet.

• Bachelor’s degree or equivalent practical experience.
• 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
• Experience in machine learning research, or quantitative research in fields such as mathematics, physical sciences, engineering, or economics.
• Experience with machine learning frameworks (e.g., JAX or PyTorch).