ML Engineer
Responsibilities: Design, implement, and maintain cloud-native infrastructure and deployment pipelines using Infrastructure as Code.
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
Posted July 25, 2026