Join Synthflow.ai, where we're innovating in AI technology to make it accessible and actionable for businesses of all sizes. Our platform is a game-changer for B2B clients, enabling them to create customized solutions with ease. We're expanding our team and looking for a skilled Python Developer who is enthusiastic about contributing to our next-generation products.

Role Summary: As a DevOps Engineer specializing in MLOps and LLM Ops, you will ensure the robustness and efficiency of our infrastructure that supports AI-driven speech technology platforms and large language models. You will collaborate closely with machine learning teams to streamline the deployment, monitoring, and maintenance of complex models that enhance our products' capabilities.

Key Responsibilities:

• 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.

Who You Are:

• 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.

Minimum Qualifications:

• 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 ML and LLM frameworks.