AI/ML Observability Intern

Summary: Leidos is seeking a motivated and curious AI/ML Observability Intern to join their Enterprise Observability Team within the Chief Data & Analytics Office. This internship provides a unique opportunity to gain hands-on experience with enterprise-grade observability platforms and learn how AI/ML is applied to improve system reliability and performance. Responsibilities: - Learn Observability Fundamentals: Gain a deep understanding of the three pillars of observability (logs, metrics, traces) and how they are used to monitor complex systems - Assist with Telemetry Data Tasks: Help with validating, documenting, and exploring new data sources as they are onboarded into our observability platforms - Contribute to Dashboards & Visualization: Assist senior engineers in building and refining dashboards that provide clear insights into system health and performance - Support AI/ML Model Lifecycle: Assist data scientists with tasks related to model creation, implementation, and deployment, such as data preparation, feature exploration, and validating model results for observability use cases - Explore AI Observability: Learn how AI/LLM applications are monitored by assisting with the instrumentation and analysis of telemetry from tools like Langfuse - Contribute to Automation: Help write and refine simple scripts (primarily in Python) to automate data quality checks or reporting tasks - Contribute to Documentation: Help create and update documentation for tools, processes, and team projects Required Qualifications: - Currently enrolled in an accredited Bachelor's or Master's degree program in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field - US citizenship required - Basic programming or scripting knowledge (Python is strongly preferred) - Academic or project-based exposure to data analysis or machine learning concepts - A strong desire to learn, a proactive attitude, and excellent problem-solving skills - Ability to work collaboratively in a remote team environment Preferred Qualifications: - Coursework or projects related to machine learning, statistical modeling, or AI - Familiarity with data formats like JSON or CSV - Exposure to cloud platforms (e.g., AWS, Azure) or Linux/Unix environments - Familiarity with version control using Git Required Skills: Python, Machine learning, Data analysis, JSON, CSV, AWS, Azure, Linux, Unix, Git Benefits: Competitive compensation, Health and Wellness programs, Income Protection, Paid Leave, Retirement