Senior AI Research Scientist — Frontier Models

Cisco Systems, Inc.; San Francisco (CA); On-site; USD 210,000 - 320,000; Full time

Job summary

Cisco Systems, Inc. and Foundation AI collaborate to advance frontier AI research, translating research into scalable, enterprise-grade AI solutions.

The AI Researcher will design experiments, develop methods for pre-training and post-training, and turn insights into practical systems with robust infrastructure. Ideal candidates bring deep expertise in algorithm design for training, scalable data curation, and reliable AI infra, plus publication history in top conferences.

Qualifications

• Bachelors plus 5 years related experience in CS/AI/ML
• Strong experience with Python, PyTorch, prod-grade software engineering practices
• Experience with large language models, training, fine-tuning, evaluation, inference, and optimization
• Strong understanding of data pipelines, model experimentation, and scalable AI system design
• Strong communication skills to explain complex research and engineering concepts to cross-functional partners

Responsibilities

• Develop scalable data curation and processing methods that improve model training and task-specific performance.
• Build production-ready AI systems using strong software engineering practices.
• Optimize large language models and agentic systems for enterprise and security-focused use cases

Skills

Python

PyTorch

Production-grade software

AI/ML libraries

LLMs

Data pipelines

Model experimentation

Communication skills

Education

Bachelor's degree in Computer Science or related field

Master's degree in Computer Science or related field

PhD in relevant field

Tools

Docker

Kubernetes

NVIDIA Triton

TorchServe

vLLM

AWS

GCP

Azure

Job description

Cisco Systems, Inc. and Foundation AI collaborate to advance frontier AI research, translating research into scalable, enterprise-grade AI solutions.

The AI Researcher will design experiments, develop methods for pre-training and post-training, and turn insights into practical systems with robust infrastructure. Ideal candidates bring deep expertise in algorithm design for training, scalable data curation, and reliable AI infra, plus publication history in top conferences.