Data Science Intern: ML, LLMs & Cloud Analytics

Apexanalytix; Greensboro (NC); On-site; USD 28,000 - 41,000; Part time

Job summary

apexanalytix seeks a Data Science Intern to develop and deploy data analytics and AI applications, build machine learning models, and deploy into Kubernetes clusters, handling large datasets and monitoring.

You will join a dynamic team, gain hands-on experience with Docker, Kubernetes, and Streamlit, and help prototype AI-powered features while staying current with industry trends. This internship offers practical, hands-on exposure to real-world cloud computing and analytics challenges.

Qualifications

• Pursuing a bachelor's degree or higher in CS/DS/Math/Engineering or related field.
• Strong Python programming for data analysis or data science.
• Experience with data analysis and ML model development.
• Experience with SQL and database management systems.
• Knowledge of Large Language Models (LLMs) and their AI applications.
• Familiarity with Docker and Kubernetes for containerized apps.

Responsibilities

• Process and analyze complex data from diverse sources to extract insights.
• Build and deploy machine learning models.
• Design, develop, and deploy containerized apps to Kubernetes.
• Ensure scalability, reliability, and performance of deployed apps.
• Work with LLMs to develop AI-powered features.
• Troubleshoot AI applications and ML models and the relevant tools/platforms.
• Build UI apps using Streamlit or a similar framework to prototype and gather user feedback.
• Stay up to date with industry trends, best practices, and emerging technologies in AI, data science, and cloud computing.

Skills

Python

Data analysis

Machine learning

SQL

LLMs

Communication

Education

Bachelor's degree or higher in CS/DS/Math/Engineering or related field

Tools

Docker

Kubernetes

Streamlit

Job description

apexanalytix seeks a Data Science Intern to develop and deploy data analytics and AI applications, build machine learning models, and deploy into Kubernetes clusters, handling large datasets and monitoring.

You will join a dynamic team, gain hands-on experience with Docker, Kubernetes, and Streamlit, and help prototype AI-powered features while staying current with industry trends. This internship offers practical, hands-on exposure to real-world cloud computing and analytics challenges.