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