Audio Inference Engineer, Model Efficiency

Cohere(2 months ago)

HybridFull TimeSenior$179,069 - $239,068 (estimated)Modeling

About this role

The Audio Inference Engineer for Model Efficiency at Cohere is responsible for optimizing audio model serving efficiency by enhancing core metrics such as latency, throughput, and quality. This role involves identifying bottlenecks in existing systems and implementing innovative solutions for audio processing and streaming workloads. Collaboration with training and serving infrastructure teams is essential to ensure seamless integration of model development and real-time audio inference deployment. Candidates should have significant experience in high-performance audio or machine learning inference systems, with proficiency in C++ and Python, and a focus on achieving results.

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Required Skills

Machine Learning
Audio Processing
System Optimization
C++
Python
Deep Learning
Streaming Architecture
Model Parallelization
Inference Frameworks
Sequence Modeling

+4 more

About Cohere

cohere.com

Sanity is a platform that provides flexible content management solutions tailored for developers, marketers, and content creators. By utilizing a real-time collaborative editor and structured content, it allows users to build and manage high-performance applications and websites. Sanity’s APIs and flexible data model enable seamless integration with various frameworks and technologies, empowering users to deliver customized content experiences. With features like query-driven content fetching and an extensible plugin system, Sanity is designed to enhance productivity and scalability for teams of all sizes.