A Machine Learning Engineer specializes in designing, building, and deploying machine learning models. They utilize statistical and mathematical techniques, parallelizing processing, hyperparameter tuning, and other optimization methodologies to improve model performance. Responsibilities also include collecting and preprocessing large datasets, conducting exploratory data analysis, working closely with data engineers to understand data requirements, and engineer input variables for machine learning models.
Machine Learning Engineer aqua IT Springfield, VA Job Details Full-time 4 hours ago Qualifications Version control Software engineering Predictive modeling analysis Continuous Delivery (CD) implementation Application Architecture Design (Architecture design skill) Software testing Design (software development lifecycle) Data analysis software Providing code feedback
Full 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
