Machine Learning Engineer, Audio

Sandbar; New York (NY); On-site; USD 120,000 - 170,000; Full time

Job summary

Sandbar, an interface company in New York City, is building Stream, a private voice ring and conversational interface, to augment human thinking and action. We seek a machine learning engineer to develop a system spanning voice, memory, and agentic control for real-world ML deployment and human-in-the-loop interaction.

Responsibilities include developing STT/TTS models across cloud and on-device settings, optimizing inference pipelines for latency and reliability, and collaborating with ML/AI

Qualifications

• 4+ years of machine learning experience.
• Experience developing audio/voice models.
• Experience shipping ML-based products.

Responsibilities

• Develop, evaluate, and deploy STT/TTS models spanning cloud models to resource-constrained on-device settings.
• Optimize inference pipelines for latency, reliability, and concurrency.
• Work closely with other ML/AI engineers, infrastructure engineers, designers, and cofounders on existing and future products.

Skills

ML experience

Audio/Voice models

ML deployment

Job description

Sandbar is an interface company in New York City. We aim to augment individuals so we can each think, act, and move more freely. Our team has built SW, ML, and HW products across Meta, CTRL-labs, Google, Apple, Fitbit, Peloton, and Equinox.

Our first product, Stream, is a self extension—a private voice ring and conversational interface. Stream has been featured in WSJ, Bloomberg, & Wired, and begins shipping in Summer '26.

Join us in creating technology that extends human thinking.

The Role

We’re looking for a machine learning engineer to help build Stream, a new conversational computer. As a machine learning engineer, you will develop a system which spans voice, memory, and agentic control. This role is perfect for someone cares deeply about real-world ML deployment and human-in-the-loop agentic interactions.

Responsibilities

• Develop, evaluate, and deploy STT/TTS models spanning cloud models to resource-constrained on-device settings
• Optimize inference pipelines for latency, reliability, and concurrency
• Work closely with other ML/AI engineers, infrastructure engineers, designers, and cofounders on existing and future products

Qualifications

• 4+ years machine learning experience
• Experience developing audio / voice models is required
• Experience shipping ML-based products is required