Machine Learning Engineer, Ops

About the Role:

We are looking for an MLOps Engineer to build and scale the inference infrastructure for our generative audio models, including Text-to-Speech (TTS), voice conversion, and Automatic Speech Recognition (ASR). You will be responsible for designing and deploying high-performance systems that ensure low-latency, reliable, and scalable model serving for both streaming and batch inference. This role is central to bridging the gap between research and production, ensuring our audio models are optimized for performance and cost-efficiency as we scale.

What You’ll Do:

• Design and maintain inference infrastructure for generative audio model architectures.

• Implement and manage high-performance inference engines.

• Orchestrate service deployments using Kubernetes (K8S), implementing advanced autoscaling paradigms to handle varying traffic loads efficiently.

• Develop and automate robust CI/CD pipelines to streamline the testing and deployment of model artifacts and inference configurations.