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Twin Health

Delivers digital twin for metabolic health.

Senior AI Platform Engineer

Applied Machine LearningUpdated on Nov 13
Full-timeRemote in USA

About the Job

Requirements

  • A bachelor's or master's degree in Computer Science, Engineering, or a related field, with at least five years of industry experience.
  • Familiarity with architectural frameworks for large, distributed, high-scale machine-learning applications.
  • A solid understanding of MLOps, data structures, and software design principles.
  • Proficiency in Python and experience with another language such as Java or Go.
  • Strong knowledge of deploying scalable machine-learning models, including Docker, Kubernetes, and microservices architecture.

Responsibilities

  • Architect, design, and build robust, efficient AI/ML systems for production, focusing on backend distributed systems, microservices, and system accuracy.
  • Lead cross-functional initiatives end-to-end, including scoping, timelines, and dependencies, and drive alignment across Data, Infrastructure, and ML Engineering.
  • Collaborate with AI/ML engineers to optimize workflows for model training, real-time inference, monitoring, and troubleshooting.
  • Serve as a subject matter expert on ML infrastructure, providing guidance to internal teams and external stakeholders.
  • Ensure operational excellence and reliability of ML systems, and define and enforce SLAs for system performance, including latency, throughput, and resource utilization.
  • Develop tools for model management and continuous monitoring, and improve efficiency and effectiveness across the ML lifecycle.
  • Engage in mentorship and knowledge sharing to promote continuous learning and improvement within the team.

Desired Qualifications

  • Experience implementing applications using LLMs and generative AI is a significant plus.
  • Experience with database technologies such as SQL and NoSQL, and big data processing frameworks such as Spark, is a plus.

About the Company

Twin Health

Delivers digital twin for metabolic health.

Twin Health uses the Whole Body Digital Twin to monitor metabolism in real time and personalize treatment for chronic metabolic diseases like diabetes. Clients subscribe to the platform and receive medical coaching; sensors feed data to an AI model that builds a virtual body and guides interventions. It differentiates itself by targeting the root metabolic dysfunction with continuous sensing, AI insights, and partnerships with healthcare providers and insurers. The goal is to reverse and prevent metabolic diseases by restoring healthy metabolism through scalable, subscription-based care.

Company size
501-1,000
Company stage
Series E
Total funding
$286.5M
Headquarters
Menlo Park, CA
Founded
2018

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