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Tier-1 employer, generalist 'Software Engineer' title, metro locations increase qualified applicant density.
Highly specialized ML systems and AI infrastructure skills limit cross-industry transferability.
Explicit 8+ years requirement, specific tech and cloud/ML infrastructure expertise.
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Build and maintain distributed AI platform services supporting large-scale reinforcement learning and model training workflows.
Lead architecture, design, and implementation of scalable, secure, and performant cloud-based AI infrastructure features.
Drive reliability and operational excellence including live site support, incident response, and continual improvement through telemetry and automation.
Bachelor's degree in Computer Science, Computer Engineering, or related field with 8+ years of software engineering experience; OR Master's degree with 5+ years experience; OR equivalent experience.
Proficient in .Net, Java, Azure Functions, Docker, Python, and experience with distributed, cloud-based software services.
Ability to meet Microsoft and customer security screening requirements, including Microsoft Cloud background check.
Passion for machine learning, AI, and data science.
Experienced in designing and operating large-scale AI or machine learning cloud services, preferably on Microsoft Azure.
Demonstrated expertise in agile development, CI/CD practices, and performance optimization for complex distributed systems.
Capable of independently driving design decisions, troubleshooting production incidents, and enhancing platform scalability and reliability.