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Develop and manage a scalable and secure infrastructure for deploying TTS, STT, and LLM applications.
Create and maintain CI/CD pipelines for continuous integration and deployment of various AI models.
Work alongside ML engineers to optimize the training, validation, and deployment of speech and language models.
Monitor and analyze system performance and resolve any issues to ensure reliability and efficiency.
Innovate and implement best practices in cloud technology, containerization, and MLOps/LLM Ops tools to advance our operational capabilities.

Experienced in DevOps, with a deep focus on MLOps and experience in LLM Ops.
Proficient with cloud services (AWS, GCP, Azure) specifically for deploying ML and LLM environments.
Expertise in container technologies such as Docker and orchestration tools like Kubernetes.
Strong communication skills, capable of collaborating effectively with both technical and non-technical teams.

Bachelor’s degree in Computer Science, Engineering, or a related technical field.
Minimum of 3 years experience in DevOps, with significant exposure to MLOps and preferably LLM Ops.
Strong programming and scripting skills in languages like Python.
Demonstrated ability in infrastructure management, DevOps, and operations for

DevOps Engineer (ML-Ops)

Anywhere in the world