AI Researcher

About the role

At Foundation AI, we are leading frontier AI research across Cisco. Our mission is to advance the state of AI. We translate that research into purpose-built models, agentic systems, new algorithms, optimization methods, and scalable data processing techniques that solve real-world problems at scale. We explore new model architectures, pre-training and post-training methods, inference optimization, evaluation techniques, and data pipelines. Together, we are advancing AI at Cisco and for the broader AI community!

Responsibilities

• Work on the research, development, and deployment of advanced AI systems.
• Focus on large language models, agentic AI, multimodal learning, and enterprise-scale AI applications.
• Help translate frontier research into practical systems by designing experiments, developing new methods, and turning research insights into impactful, scalable AI solutions.
• 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.
• Write scientific articles for top-tier machine learning and AI conferences, publish technical blog posts, and contribute to the open-source AI community.
• 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.

Requirements

• Bachelor's + 7 years of related experience, or Master's + 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.

Benefits

We offer competitive salaries, comprehensive benefits, and a supportive work environment. Specific details are available upon request.

Pay

The full salary range for certain locations is listed below. For locations not listed, the recruiter can share more details about compensation for the role in your location during the hiring process.

Schedule

Our schedule is flexible to accommodate your needs while ensuring productivity and collaboration.