Senior AI Researcher
$216,300–$280,800 year
On-siteSan Francisco, California, United States
Job Summary
Define and direct multi-year research programs aligned with Foundation AI's strategic priorities, setting the technical bar and research methodology for the wider team. Invent and pioneer novel architectures and algorithms for foundation model training and inference, complex reasoning agentic AI systems, and multimodal learning. Drive frontier research in advanced domains such as reinforcement learning, mechanistic interpretability, and scaling laws, with applications to the cybersecurity domain. Design and build new evaluation benchmarks and frameworks that improve the reliability, transparency and safety of AI models. Collaborate across research, engineering, product, and security teams to translate research into production AI systems and drive the adoption of the new research across Cisco's AI portfolio. Mentor researchers, engineers and interns, elevating the team's scientific rigor and engineering excellence through code reviews, paper reviews, and architectural guidance. Publish research in top AI conferences and journals, contribute to open-source AI projects, and represent Cisco through invited talks and technical collaborations.
Required Qualifications
- PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field
- 5+ years of relevant research experience
- equivalent demonstrated research impact
- Demonstrated track record of sustained, high-impact publications at top-tier machine learning and AI conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, ICCV, or equivalent venues)
- Deep expertise in foundation models, post-training and alignment, LLMs, agentic AI, reinforcement learning, reasoning, efficient inference, or distributed training systems
- Expert-level proficiency in Python, PyTorch, distributed machine learning, and modern AI research frameworks
- Proven ability to lead complex, ambiguous technical projects from conception to deployment as an individual contributor
- Exceptional ability to communicate complex scientific concepts to both highly technical peers and non-technical executive stakeholders
Desired Qualifications
- Hands-on expertise in high-performance computing environments, with a track record of leading distributed training across thousands of GPUs using frameworks and communication primitives such as CUDA, NCCL, FSDP2, and Megatron-LM
- Experience deploying high-performance inference engines such as vLLM and SGLang, and working with cloud-native deployment, Docker, Kubernetes, MLOps pipelines, and major cloud platforms such as AWS, GCP, or Azure
- 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
- Demonstrated leadership within the global AI research community, specifically serving as an Area Chair or senior program committee member for top-tier AI conferences
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.