Machine Learning Engineer

Aqua IT; Springfield (VA); On-site; USD 120,000 - 150,000; Full time

Job summary

Aqua IT in the United States seeks a skilled DevOps engineer to design, implement, and maintain cloud-native infrastructure and deployment pipelines using Infrastructure as Code. You will lead architecture across multiple cloud environments and build scalable, secure solutions.

This role emphasizes full-stack development, operational excellence, monitoring, and security-first design, with mentorship of team members in DevOps best practices and cloud-native technologies.

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

Job description

Description of Services/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

Basic Requirements

• - Active TS/SCI required
• - 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 Qualifications:

• - 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