AI Research Scientist PhD (Intern) - United States
External
Cisco · San Francisco, CAPrepare for this interview
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Requirements
- Currently enrolled in a PhD program in Computer Science, Artificial Intelligence, Machine Learning, or a related field .
- Strong understanding of machine learning, deep learning, and natural language processing concepts, validated through academic, project, or professional work.
- Experience training large language models (LLMs)-including modeling, optimization, fine-tuning, and serving-using Python and common AI libraries (e.g., TensorFlow, PyTorch , Hugging Face Transformers), evidenced through academic, project, or professional work.
- Familiarity with agentic AI concepts, agent frameworks, and related applications.
- Proficiency in software development, with experience in relevant programming languages (such as Python and Go) and associated tools.
- Experience working with inference engines (e.g., vLLM , Triton, TorchServe ) for LLM serving and optimization.
- Familiarity with containerization and cloud platforms (such as Docker and AWS), as well as distributed systems for scaling and deploying AI models.
- Why Cisco?
- We are Cisco, and our power starts with you.
- Message to applicants applying to work in the U.S. and/or Canada:
- The starting salary range posted for this position is $44,000.00 to $130,000.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.
- U.S. employees are eligible for paid t
Benefits
Additional Information
The application window is expected to close on: 06/23/2026 Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received . Applications are accepted until 6/23/2026. This role may be eligible for remote work in the United States depending on business needs and hiring manager approval. Meet the Team Join a collaborative team of researchers and engineers dedicated to unlocking insights from substantial volumes of structured, unstructured, transactional, and real-time data. Together, we analyze diverse data sources to understand customer usage patterns and deliver actionable, impactful insights using advanced metrics, algorithms, and statistical techniques.
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