Audio AI Researcher: Multimodal, Low-Latency Modeling

Mosaic.tech; San Francisco (CA); On-site; USD 350,000 - 475,000; Full time

Benefits offered by this job

Health benefits

Dental benefits

Vision benefits

Unlimited PTO

Parental leave

Relocation support

Job summary

Thinking Machines Lab in San Francisco is actively researching audio capabilities, blending rigorous theory with practical engineering to build multimodal AI systems. You will work across pre-training, post-training, and product to develop models that understand and generate audio with high fidelity and low latency.

The role requires deep experimentation, code writing, and collaboration with researchers, engineers, and designers to push the foundations of how AI learns and communicates.

Qualifications

• Ability to design, run, and analyze experiments with empirical rigor.
• Understanding of machine learning fundamentals and distributed compute environments.
• Proficiency in Python and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow, or JAX).
• Bachelor’s degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding.
• Clarity in communication, an ability to explain complex technical concepts in writing.

Responsibilities

• Own research projects on audio training, low‑latency inference and conversational responsiveness.
• Design and train large-scale models that natively support audio input and output.
• Investigate scaling behavior such as how data, model size, and compute affect capability and efficiency.
• Build and maintain audio data pipelines, including preprocessing, filtering, segmentation, and alignment for training and evaluation.
• Collaborate with data and infrastructure teams to scale audio training efficiently across distributed systems.
• Publish and present research that moves the entire community forward. Share code, datasets, and insights that accelerate progress across industry and academia.

Skills

Experiment design

ML fundamentals

Python & DL frameworks

Communication skills

Education

Bachelor’s degree or equivalent

PhD (preferred) in CS/ML/Physics/Math

Tools

PyTorch

TensorFlow

JAX

Job description

Thinking Machines Lab in San Francisco is actively researching audio capabilities, blending rigorous theory with practical engineering to build multimodal AI systems. You will work across pre-training, post-training, and product to develop models that understand and generate audio with high fidelity and low latency.

The role requires deep experimentation, code writing, and collaboration with researchers, engineers, and designers to push the foundations of how AI learns and communicates.