The Leidos Cyber Accelerator is redefining how we build, validate, and scale next-generation cyber and artificial intelligence (AI) capabilities. We are seeking an AI/ML Intern to support Cyber AI projects.  

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‚ÄčThe ideal candidate is passionate about a broad range of projects from research & development to prototype development, culminating in deployment of our products to customers. This role works alongside junior and senior engineers and research scientists with expertise in machine learning, cybersecurity, IT, reverse engineering, and Cyber AI. The successful candidate will have experience in areas like: software engineering, artificial intelligence (AI), cybersecurity, and machine learning (ML).¬†

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‚ÄčPrimary Responsibilities¬†

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• ‚ÄčAssist in the design, implementation, and evaluation of AI/ML models for various applications.¬†

• ‚ÄčCreate AI/ML prototypes for various use cases¬†

• ‚ÄčEnhance and maintain analysis tools, including automation of current processes using AI/ML algorithms¬†

• ‚ÄčApply existing knowledge and acquire new skills to help solve complex problems, all while gaining experience in the development and delivery of solutions to customers¬†

• ‚ÄčWork within a multidisciplinary team to design and develop solutions¬†

• ‚ÄčEffectively communicate with engineers regarding current tasks and present findings to provide actionable insights¬†

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‚ÄčBasic Qualifications¬†

• ‚ÄčCurrently enrolled in a master's degree or PHD program in Data Science, Computer Science, Artificial Intelligence, Mathematics, Statistics, Computer Engineering or STEM-related degree¬†

• ‚ÄčHands-on Software Development Skills (Python-Preferred)¬†

• ‚ÄčUnderstanding of machine learning algorithms, tools and platforms (Familiarity with tools like NumPy, SciPy, scikit-learn, TensorFlow, Pytorch, LLM ecosystems (RAG,¬† agentic systems) or similar.)¬†

• ‚ÄčDemonstrate problem solving, teamwork, and communication skills¬†

• ‚ÄčAbility to obtain a DoD security clearance - US Citizenship required.¬†

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‚ÄčPreferred Qualifications¬†

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• ‚ÄčExperience developing production solutions leveraging large language models (LLMs).¬†

• ‚ÄčExperience with cloud platforms (AWS, Azure) for deploying machine learning models.¬†

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