Audio Inference Engineer, Model Efficiency at Cohere

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Improve latency, throughput and quality of real-time audio model inference at Cohere. The remote-friendly Model Efficiency team prefers overlap with Eastern or Pacific time zones.

Cohere

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Location: Remote
Advertised region: New York / San Francisco / Toronto / Montreal / United States
Employment: FullTime
Work arrangement: remote
Technologies: Python, C++, PyTorch, TensorFlow

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Role overview

Improve latency, throughput and quality of real-time audio model inference at Cohere. The remote-friendly Model Efficiency team prefers overlap with Eastern or Pacific time zones.

Responsibilities

Find bottlenecks in speech and audio serving systems.
Optimize streaming inference and coordinate changes with model training and serving infrastructure teams.
Measure performance and quality of deployed audio workloads.

Qualifications

Experience building high-performance audio or ML inference systems.
C++ or Python skills and practical work with deep-learning models for speech, audio or language.

Technology in this role

Python: C++ or Python skills and practical work with deep-learning models for speech, audio or language.

About Cohere

Cohere builds foundation AI models and enterprise AI products.

Employer website

How to apply

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Source checked: 2026-11-08

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