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Summer 2026 INTERN - Machine Learning
Location
United States
Posted
4 days ago
Salary
$27 / hour
Seniority
Entry Level
No structured requirement data.
Job Description
Summer 2026 INTERN - Machine Learning
Iron Mountain
Role Description Iron Mountain is seeking a motivated Global Platforms & Technology Machine Learning Intern to join our AI Services team. In this role, you will be responsible for developing and optimizing applied AI systems, including Large Language Model (LLM) applications and Agentic platforms, to solve real-world enterprise challenges. What You’ll Do - Develop and implement AI features for Agentic platform, focusing on System APIs and long-term enterprise software development. - Collaborate with cross-functional engineering leads and peer groups environment to scale AI products for global enterprise use cases. - Ensure compliance with core computer science fundamentals such as data structure and algorithms, theory of computation, discrete mathematics, and software engineering by writing clean, efficient code in Golang or JVM languages. Qualifications - Current enrollment in a Computer Science or related Bachelor’s (rising junior or senior only) or Master’s degree program graduating May 2027 OR after May 2028. - Strong knowledge of Machine Learning including deep Learning, NLP, and Reinforcement Learning, core algorithms, and mathematics. - Proven ability in Golang or JVM languages (Java/Kotlin), with experience in API services development and a high-level proficiency of Python. - Data engineering background in applications such as batch processing and query engineering is a significant plus. - US Citizenship required; please note that we are unable to provide sponsorship for this position. Requirements - Strong programming skills in Golang or JVM languages. - Understanding of core computer science fundamentals. - Experience in developing AI features and API services. Benefits - Salary details: $27.00 per hour. - Shifts: Standard business hours during the program. - Location: Tampa, FL or remote. - Competitive compensation and benefits aligned with the experience. - Paid time off/holidays according to regional intern policy. - Flexible work options to support work–life balance.
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Sr AI/ML Engineer
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• Design, develop, and deploy AI/ML solutions to modernize core pharmacy platforms, with a focus on scalability, reliability, performance, and security • Leverage Generative AI, LLMs, and agentic AI frameworks to automate and enhance pharmacy workflows and decision-making processes • Collaborate with business and technical stakeholders to understand pharmacy domain requirements and translate them into robust AI/ML-driven technical solutions • Contribute to architecture and technical design of AI/ML pipelines, including model selection, data integration, and deployment patterns • Establish and maintain AI/ML engineering standards, best practices, and quality assurance processes • Conduct code reviews, provide constructive feedback, and mentor engineers on modern AI/ML engineering practices • Partner with cross-functional teams including data scientists, product managers, platform engineers, and pharmacy domain experts • Translate legacy system modernization needs into scalable AI applications that enhance products, workflows, and operational efficiency • Monitor and optimize AI/ML model performance, resource utilization, and platform reliability • Collaborate with DevOps and infrastructure teams to ensure secure, scalable deployment and operations of AI/ML solutions • Stay current with advancements in AI/ML frameworks, Generative AI, LLMs, and pharmacy technology modernization
• Designing, building, and delivering highly scalable big data and ETL solutions across distributed environments. • Supporting projects at various and unanticipated client worksites throughout the United States. • Working closely with cross-functional teams to develop, test, and deploy data solutions that meet business and operational needs. • Leveraging modern big data frameworks, cloud platforms, and agile development practices. • Preparing technical design documentation for implemented solutions. • Identifying and resolving data pipeline issues and providing timely solutions.



