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Santa Clara, CA

Internship

Onsite

$26/hr - $51/hr

Intern

Marvell Technology is a leading provider of semiconductor solutions crucial for data infrastructure across various domains. They are seeking an AI Platform Engineer Intern to join their AI Development Team, focusing on Agentic AI, where the intern will design, implement, and optimize AI agents and frameworks while collaborating with cross-functional teams.

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Responsibilities

Lead the design and development of Agentic AI applications and workflows for real-world use cases.
Conduct research and experiments on new AI agent architectures and orchestration strategies.
Implement and optimize machine learning models and agent pipelines for performance and scalability.
Develop prototypes and proof-of-concept AI agents capable of performing multi-step tasks.
Benchmark and analyze the performance of existing AI agents, proposing enhancements to improve reliability and effectiveness.
Work with data engineers and software developers to integrate agents into larger platforms and applications.
Support the development of secure and compliant agent-based workflows that handle sensitive data.
Stay up-to-date with advancements in agentic AI, machine learning, and automation frameworks and apply them to ongoing projects.

Qualification

Required

Currently pursuing a degree in Data Science, Computer Science, Mathematics, Statistics, or a related field.
Proficiency in programming languages such as Python, R, or Java.
Solid understanding of machine learning concepts, algorithms, and frameworks (e.g., TensorFlow, PyTorch).
Prior exposure to data analysis, statistical modeling, and experimental design.
Knowledge of software development best practices, including version control (e.g., Git).
Strong problem-solving skills and ability to work in a collaborative team environment.

Preferred

Previous experience with AI/ML projects, especially agent-based AI development.
Familiarity with advanced topics such as deep learning, reinforcement learning, or natural language processing.
Exposure to agent orchestration frameworks (e.g., LangChain, CrewAI, Semantic Kernel).
Familiarity with cloud computing services (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes).
Understanding of DevOps principles and experience with CI/CD pipelines.
Experience optimizing machine learning models for deployment and scalability.
Familiarity with research tools and libraries (e.g., SciPy, Keras, Hugging Face Transformers).