Senior Staff Applied AI Scientist

Cisco Systems, Inc. • San Diego, CA

42d

About The Position

Splunk, a Cisco company, is building a safer, more resilient digital world with an end‑to‑end, full‑stack platform designed for hybrid, multi‑cloud environments. Join the Foundational Modeling team at Splunk, where we advance the state of AI for high‑volume, real‑time, multi‑modal machine‑generated data - including logs, time series, traces, and events. We combine deep AI research expertise with the scale and operational excellence of Splunk and Cisco's global engineering capabilities. Our work spans networking, security, observability, and customer experience - designing and deploying foundation models that enhance reliability, strengthen security, prevent downtime, and deliver predictive insights across Splunk Observability, Security, and Platform at enterprise scale. You'll be part of a culture that values technical excellence, impact‑driven innovation, and cross‑functional collaboration - all within a flexible, growth‑oriented environment.

Requirements

• PhD in Computer Science, or related quantitative field, plus 5+ years of industry research experience.
• Proven track record in at least one of the following areas: large language modeling for both structure and unstructured data, deep learning‑based time series modeling, advanced anomaly detection, and multi-modality modeling.
• Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow)
• Experience translating research ideas into production systems.

Nice To Haves

• Deep NLP & Domain‑Adapted LLMs: Background in building and adapting large‑scale language models (e.g., T5, BERT, LLaMA) for specialized domains including structured/unstructured logs, text, and event sequences.
• Log Analytics Expertise - In‑depth knowledge of structured/unstructured system logs, event sequence analysis, anomaly detection, and root cause identification.
• Advanced Anomaly Detection - Experience creating robust, scalable approaches (statistical, deep learning, or hybrid) for high‑volume, real‑time logs data.
• Multi‑Modal AI Modeling - Strong track record fusing logs, time series, traces, tabular data, and graphs for foundation models tackling complex operational insights.
• Large‑Scale Training & Optimization - Experience optimizing model architectures, distributed training pipelines, and inference efficiency to minimize cost and latency while preserving accuracy.
• MLOps & Continuous Learning - Fluency in automated retraining, drift detection, incremental updates, and production monitoring of ML models.
• Strong Research Track Record - Publications in top AI/ML conferences or journals (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR, ACL, KDD) demonstrating contributions to state‑of‑the‑art methods and real‑world applications.

Responsibilities

• Own the full lifecycle of research, design, and deployment for large‑scale foundation models targeting machine‑generated data - with a primary focus on logs, complemented by time series, traces, and event modalities.
• Drive optimization of distributed training and inference pipelines to balance accuracy, performance, and cost at scale.
• Partner closely with engineering, product, and data science teams to align AI solutions with both technical requirements and strategic business objectives.
• Elevate organizational expertise by mentoring talent, driving strategic technical forums, and guiding research from inception to product deployment.
• Shape the AI/ML vision by anticipating industry‑defining advancements and strategically embedding them into the team's technology roadmap.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Industry: Professional, Scientific, and Technical Services
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees