Senior MLOps Engineer

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Twin Health is seeking a Senior MLOps Engineer to build robust AI/ML systems for its digital twin platform that helps prevent and improve chronic metabolic diseases. The role involves architecting distributed backend systems, optimizing model training and real-time inference, and ensuring operational excellence across the ML lifecycle. You will collaborate with data, infrastructure, and ML engineering teams to scale MLOps practices in a fast-growing health tech startup.

• Architect, design, and build robust and efficient AI/ML systems for production, focusing on backend distributed systems, microservices, and system accuracy.
• Lead cross-functional initiatives end-to-end (scoping, timelines, dependencies), driving alignment across Data, Infra, and ML Engineering.
• Collaborate with AI/ML engineers to optimize workflows for model training, real-time inference, monitoring, and troubleshooting.
• Act as a subject matter expert on ML infrastructure, providing guidance to internal teams and external stakeholders.
• Ensure operational excellence and reliability of ML systems, defining and enforcing SLAs around performance, latency, throughput, and resource utilization.
• Develop tools for effective model management, continuous monitoring, and enhancing ML lifecycle efficiency.
• Actively mentor and share knowledge to promote a culture of continuous learning and improvement.