AI/ML Engineer

Responsibilities: Design, implement, and maintain cloud-native infrastructure and deployment pipelines using Infrastructure as Code. Lead and architect scalable, secure, and resilient infrastructure solutions across multiple cloud environments. Build and optimize CI/CD pipelines for complex microservices architectures. Develop and maintain full-stack applications while ensuring operational excellence and reliability. Implement monitoring, logging, and alerting solutions for production systems. Drive security-first infrastructure design and implementation. Mentor team members on DevOps best practices and cloud-native technologies Requirements: Must be willing to work in SCIF daily or as needed, and participate in on-call rotation for production support as needed Bachelor's degree or above in Science, Technology, Engineering, or Mathematics (STEM) Experience in professional software engineering & best practices for the full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence 3+ years of machine learning/statistical modeling data analysis tools and techniques Preferred (but not required): Master's degree or above in Science, Technology, Engineering, or Mathematics (STEM) Experience working on multi-team, cross-disciplinary projects Experience applying quantitative analysis to solve business problems and making data-driven business decisions Experience in defining and creating benchmarks for assessing GenAI model performance Experience with Python, SQL/NoSQL, and API development for building and deploying AI/ML solutions Experience working with Large Language Models (LLMs), prompt engineering, and generative AI frameworks