SAP Ariba iXp Intern – AI Machine Learning
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Job Description
About the Company:
SAP is a global leader in providing enterprise application software, serving a wide array of industries including consumer, discrete manufacturing, and public services. Founded in 1972, the company is headquartered in Walldorf, Baden-Wurttemberg, Germany. With a substantial workforce of over 10,001 employees, SAP operates as a Public Company. Notably, SAP has a history of offering H1B sponsorships.
Job Description:
The role is for an SAP Ariba iXp Intern – AI Machine Learning. This position is focused on the development and delivery of innovative AI algorithms within SAP Ariba, requiring close collaboration with senior engineers. The core objective is to translate artificial intelligence algorithms from their conceptual stage into production-ready solutions, emphasizing the need for both Data Science and MLOPs (Machine Learning Operations) skill sets.
Responsibilities:
As a Core AI Machine Learning Intern, you will be an integral part of a team, working alongside Senior MLE Engineers, Senior Data Engineers, and Senior Data Scientists. Your primary responsibilities will include:
• Delivering Innovative AI Algorithms: Taking Artificial Intelligence algorithms from initial concept through to full production deployment.
• Vector Search Development: Contributing to the enhancement of next-generation search capabilities for Enterprise-based search within Ariba, with the aim of providing highly relevant search results to customers.
• Guided Buying Recommendations (GBR) Revamp: Participating in the overhaul of the GBR service, which provides personalized recommendations. This involves applying novel DevOps and MLOPs infrastructure, adhering to best practices.
• Production Deliverables: Key deliverables will include implementing Vector Search, enhancing Guided Buying Recommendations, and developing Agentic workflows for production environments.
Qualifications:
To be considered for this role, candidates must possess the following:
• Python Programming Skills: Proficiency in Python is essential.
• MLOPs Expertise: Hands-on experience with Linux and Docker containerization for Machine Learning Operations.
• Database Experience: Ability to work effectively with both Vector Databases and regular databases.
• Agentic Frameworks Familiarity: Knowledge of Agentic frameworks such as Langchain, LangGraph, and Function Calling.
• Generative Pretrained Networks (GPNs) Understanding: Familiarity with GPNs, including concepts like Knowledge Distillation, Low Rank Adaptation (LoRA), and fine-tuning.
• Academic Background: Must have completed coursework in Machine Learning, Data Science, and Statistical Machine Learning.
• Deployment Experience: Demonstrated prior experience in deploying ML models into a production environment.
• Version Control & CI/CD: Hands-on experience with using git repositories and working with CI/CD pipelines.
• Education: A Master’s Degree or a Bachelor’s Degree in Data Science, Machine Learning, or Computer Science from a top university is required.
• Eligibility: Candidates must be currently enrolled in, or recently graduated (start date within 6 months of graduation date) from a coding academy/bootcamp, apprenticeship, associate, bachelor’s, master’s, or JD/PhD program.
