AI Platform Engineer Intern (Agentic) - Master's Degree

About Marvell

Marvell’s semiconductor solutions are the essential building blocks of the data infrastructure that connects our world. Across enterprise, cloud and AI, and carrier architectures, our innovative technology is enabling new possibilities. 

At Marvell, you can affect the arc of individual lives, lift the trajectory of entire industries, and fuel the transformative potential of tomorrow. For those looking to make their mark on purposeful and enduring innovation, above and beyond fleeting trends, Marvell is a place to thrive, learn, and lead. 

Your Team, Your Impact

As a Data Science/Computer Science Intern, you will be part of our AI Development Team with a focus on Agentic AI - systems that don’t just answer questions but take meaningful actions, orchestrate workflows, and assist with complex tasks. You will contribute to the design, implementation, and optimization of AI agents and frameworks that bridge the gap between theoretical research and practical, real-world deployment. This role will give you exposure to every stage of the development lifecycle, from prototyping agent workflows to deploying production-ready solutions. You will collaborate with cross-functional teams to bring innovative, secure, and scalable Agentic AI solutions to life, applying your knowledge of machine learning, data science, and software engineering to create impactful technologies that improve business outcomes.

What You Can Expect

• 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.

What We're Looking For

Minimum Qualifications:

• 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 Qualifications:

• 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).

Expected Base Pay Range (USD)

27 - 53, $ per hour.

The successful candidate’s starting base pay will be determined based on job-related skills, experience, qualifications, work location and market conditions. The expected base pay range for this role may be modified based on market conditions.

Additional Compensation and Benefit Elements 

Marvell is committed to providing exceptional, comprehensive benefits that support our employees at every stage - from internship to retirement and through life’s most important moments. Our offerings are built around four key pillars: financial well-being, family support, mental and physical health, and recognition. Highlights for our interns: medical, dental, and vision coverage, perks and discounts, robust mental health resources to prioritize emotional well-being, and paid holidays. Additional compensation may be available for intern PhD candidates. We look forward to sharing more with you during the interview process.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status.

Any applicant who requires a reasonable accommodation during the selection process should contact Marvell HR Helpdesk at TAOps@marvell.com.

Interview Integrity 

To support fair and authentic hiring practices, candidates are not permitted to use AI tools (such as transcription apps, real-time answer generators like ChatGPT or Copilot, or automated note-taking bots) during interviews.

These tools must not be used to record, assist with, or enhance responses in any way. Our interviews are designed to evaluate your individual experience, thought process, and communication skills in real time. Use of AI tools without prior instruction from the interviewer will result in disqualification from the hiring process.

This position may require access to technology and/or software subject to U.S. export control laws and regulations, including the Export Administration Regulations (EAR). As such, applicants must be eligible to access export-controlled information as defined under applicable law. Marvell may be required to obtain export licensing approval from the U.S. Department of Commerce and/or the U.S. Department of State. Except for U.S. citizens, lawful permanent residents, or protected individuals as defined by 8 U.S.C. 1324b(a)(3), all applicants may be subject to an export license review process prior to employment.

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