Audio Modeling Engineer — Real-Time Production Inference

attention labs; San Francisco, Northern (CA, KY); Hybrid; USD 150,000 - 200,000; Full time

Job summary

attention labs is building the audio modeling stack in a fast-moving startup setting in San Francisco. You will own end-to-end lifecycle from data to production inference, shipping models that recognize who is being spoken to in real time.

You will turn research into dependable inference under real-world noise and latency constraints, design evaluation harnesses, and collaborate with founders to shape next steps for the product's audio intelligence.

Qualifications

• Strong applied ML experience with audio, speech, or signal-heavy models.
• Ability to own a model from data collection to production inference, not just notebooks.
• Fluency with modern deep learning tooling such as PyTorch and rigorous measurement.

Responsibilities

• Own the audio model lifecycle end to end: data, features, architecture, training, evaluation, and production inference.
• Build and improve models behind addressee detection and real-time decisions on who is being spoken to.
• Turn research prototypes into fast, dependable inference under real-world noise and accents.
• Design evaluation harnesses and datasets to honestly measure impact of changes.
• Work directly with founders and early customers to shape next model objectives.

Skills

Audio/speech ML

Production model lifecycle

PyTorch

Latency awareness

Tools

PyTorch

Job description

attention labs is building the audio modeling stack in a fast-moving startup setting in San Francisco. You will own end-to-end lifecycle from data to production inference, shipping models that recognize who is being spoken to in real time.

You will turn research into dependable inference under real-world noise and latency constraints, design evaluation harnesses, and collaborate with founders to shape next steps for the product's audio intelligence.