2 days ago
Santa Clara, CA, USAIntern
H1B sponsor
Responsibilities
- Monitor and analyze AI platform performance across distributed computing environments.
- Identify opportunities to optimize machine learning training and inference workloads.
- Support GPU cluster and cloud infrastructure capacity planning and resource management.
- Evaluate model deployment performance using latency, throughput, and scalability metrics.
- Troubleshoot system performance issues and infrastructure challenges affecting ML workloads.
- Collaborate with engineering teams to improve AI infrastructure and platform efficiency.
- Enhance data pipeline and storage performance for large-scale machine learning applications.
Requirements
- Currently pursuing a bachelor’s or master’s degree in Computer Science, Computer Engineering, or a related technical field, with expected graduation between Fall 2027 and Summer 2028.
- Proficiency in Python for manipulation and analysis.
- Knowledge of GPU computing, CUDA programming, networking fundamentals, and distributed systems concepts.
- Familiarity with AWS, GCP, Azure, Docker, and Kubernetes.
- Understanding of system monitoring, logging, and performance analysis concepts.
- Experience with data analysis and visualization and strong analytical and problem-solving skills.
- Exposure to machine learning workflows, model deployment, and lifecycle management.
- Strong written and verbal communication skills with the ability to present technical findings to diverse stakeholders.
- Applicants must be eligible to access export-controlled information under applicable U.S. law and may be subject to an export license review process.
Benefits
- Medical, dental, and vision coverage for interns.
- Perks and discounts, mental health resources, and paid holidays.
- Additional compensation may be available for intern PhD candidates.
- Summer 2027 internship with an expected graduation window of Fall 2027 through Summer 2028.
- Base pay is $29–$57 per hour.
Categories
About Marvell
Marvell designs and sells semiconductors for data infrastructure, including Ethernet switching and PHYs, optical and 5G connectivity, storage controllers, and custom compute silicon (ASICs/DPUs) used by cloud providers, telecom carriers, and enterprise OEMs. Its business model centers on selling chips and platform solutions and co-developing custom silicon with major customers. Founded in 1995 and headquartered in Santa Clara, it is a public company traded on NASDAQ (MRVL).