Please note this posting is to advertise potential job opportunities. This exact role may not be open today but could open in the near future. When you apply, a Cisco representative may contact you directly if a relevant position opens.
Applications are accepted until further notice.
Your Impact
As an AI Researcher, you will work on the research, development, and deployment of advanced AI systems. Your focus will span large language models, agentic AI, multimodal learning, and enterprise-scale AI applications. We are looking for researchers who will help translate frontier research into practical systems by designing experiments, developing new methods, and turning research insights into impactful, scalable AI solutions.
We are particularly interested in researchers with deep expertise in algorithm design for pre-training and post-training, scalable data curation, and reliable AI infrastructure. You will drive improvements to training algorithms, curate and optimize data at scale, and design infrastructure needed to train purpose-built models that can compete with frontier models on specific tasks aligned with Cisco's business priorities and Foundation AI's research agenda.
We place a strong emphasis on publishing research and contributing meaningfully to the AI community. In this role, you will write scientific articles for top-tier machine learning and AI conferences, publish technical blog posts, and contribute to the open-source AI community!
In this role, you will:
- 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.
Minimum Qualifications
- Bachelors + 7 years of related experience, or Masters + 4 years of related experience, or PhD + 1 year of related experience in Computer Science, Artificial Intelligence, Machine Learning, or a related field
- Strong experience with Python, PyTorch, production-grade software engineering practices, and common AI/ML libraries
- Experience with large language models, model training, fine-tuning, evaluation, inference, and optimization
- Strong understanding of data pipelines, model experimentation, and scalable AI system design
- Strong communication skills, with the ability to explain complex research and engineering concepts to cross-functional partners
Preferred Qualifications
- Experience designing scalable data curation methods and building reliable infrastructure for large-scale model training, evaluation, inference, and deployment
- Experience deploying high-performance inference engines such as vLLM, NVIDIA Triton, or TorchServe, and working with cloud-native deployment, Docker, Kubernetes, MLOps pipelines, and major cloud platforms such as AWS, GCP, or Azure
- Demonstrated history of publishing research in top-tier AI/ML conferences such as NeurIPS, ICML, ICLR, or ACL, or contributing to significant open-source AI projects
- Experience designing and scaling agentic AI workflows, multi-agent frameworks, and autonomous AI systems
- Familiarity with cybersecurity principles, AI systems for security-focused use cases, safety, and robust machine learning
