Applied AI Scientist

About the role

Join the Foundational Modeling team at Splunk, where we advance the state of AI for high-volume, real-time, multi-modal machine-generated data. You'll contribute to the research, design, and development of large-scale foundation models for machine-generated data, focusing on graph data and additional support for logs, time series, traces, and events. Your work will span networking, security, observability, and customer experience, enhancing reliability, strengthening security, preventing downtime, and delivering predictive insights across Splunk products.

Responsibilities

• Contribute to the research, design, and development of large-scale foundation models for machine-generated data, with a primary focus on graph data and additional support for logs, time series, traces, and event modalities.
• Develop and enhance distributed training and inference workflows, leveraging data-driven approaches to improve model quality, scalability, and operational efficiency.
• Collaborate with engineering, product, and data science teams to understand requirements, incorporate stakeholder feedback, and deliver AI/ML solutions that address business and technical needs.
• Share emerging ideas, technical insights, and best practices with teammates, contributing to technical discussions and helping advance team capabilities and project outcomes.
• Explore and evaluate new AI/ML techniques, tools, and methodologies, applying relevant innovations to improve workflows, solve technical challenges, and support the team’s roadmap and objectives.
• Take ownership of assigned projects and deliver high-quality results with urgency, while proactively identifying obstacles, driving resolution of technical issues, and continuously improving development processes.

Requirements

• Master's degree in Computer Science or related quantitative field, plus 2+ years of industry research experience.
• Proven track record in at least one of the following areas: Large-scale graph representation learning and Graph Neural Networks (GNNs), large language modeling for structured and unstructured data, multi-modal fusion of graph, text, log, and time-series data.
• Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow).
• Experience translating research ideas into production systems.

Preferred Qualifications

• Deep experience with graph representation learning, graph transformers, spatio-temporal GNNs, heterogeneous graphs, and knowledge-graph-augmented modeling.
• Expertise in constructing and operating on large-scale graphs, including entity graphs, service dependency graphs, topology graphs, causal graphs, or log-event graphs.
• Hands-on experience with frameworks such as PyTorch Geometric, DGL, GraphGym, GraphML systems, or custom GNN runtimes.
• Advanced Anomaly Detection with Graph: track record developing hybrid graph-temporal approaches for detecting anomalies in high-volume operational data.
• Hands-on experience developing, fine-tuning, or adapting foundation models for domain-specific data such as logs, time-series, graphs, operational telemetry, or enterprise knowledge, including representation learning across structured and unstructured modalities.
• 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 demonstrating contributions to state-of-the-art methods and real-world applications.

Benefits

At Cisco, we offer competitive salaries, comprehensive benefits, and a supportive work environment. The starting salary range for this position is $165,300.00 to $209,200.00, reflecting the projected salary range for new hires in U.S. and Canadian locations. Additional benefits include medical, dental, and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. For quota-based sales roles, the ranges provided include base pay and sales target incentive compensation combined. Employees in Illinois will participate in a unique time off program to meet local requirements.