Senior Applied AI Scientist

Position Overview

Splunk, a Cisco company, is building a safer, more resilient digital world with an end‐to‐end, full‐stack platform designed for hybrid, multicloud environments. Join the Foundational Modeling team to advance AI for high‐volume, real‐time, multimodal machine‐generated data—including logs, time series, traces, and events—by combining deep research with global engineering excellence. At Cisco, we are revolutionizing how data and infrastructure connect and protect organizations in the AI era.

Key Responsibilities

• Lead the research, design, and deployment of large‐scale foundation models for machine‐generated data, primarily focused on time series augmented with logs, traces, and events.
• Optimize distributed training and inference pipelines to maximize accuracy, performance, and efficiency.
• Collaborate with engineering, product, and data science teams to ensure solutions meet technical requirements and deliver tangible business impact.
• Mentor team members and contribute to model architecture reviews, experimental design, and production rollout processes.
• Stay current with AI/ML developments and integrate relevant advancements into ongoing projects and technical plans.

Required Qualifications

• PhD in Computer Science or a related quantitative field, plus 1+ years of industry research experience.
• Proven track record in areas such as large language modeling, deep learning‐based time series modeling, advanced anomaly detection, or multi‐modality modeling.
• Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow).
• Experience translating research ideas into production systems.

Preferred Qualifications

• Expertise in Deep Learning for Time Series & Forecasting, including work with temporal transformers, temporal convolutional networks, and spatiotemporal models.
• Experience in advanced anomaly detection using robust, scalable approaches.
• Strong background in MultiModal AI Modeling, fusing logs, time series, traces, tabular data, and graphs.
• Skills in Probabilistic Forecasting & Uncertainty Quantification, with experience in Bayesian deep learning.
• Experience with large‐scale training & optimization, including distributed training pipelines and efficient inference.
• Fluency in MLOps practices such as automated retraining, drift detection, and production monitoring of ML systems.
• A strong research track record demonstrated by publications in top AI/ML conferences or journals (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR, ACL, KDD).

Benefits & Perks

• Competitive Compensation: Starting salary range of $174,500.00 to $226,500.00 for U.S. and Canada, with additional specific ranges for locations (e.g., New York City Metro: $199,700.00 - $292,800.00, Non-Metro New York & Washington: $174,500.00 - $260,500.00). Incentive compensation details apply for sales roles.
• Robust Benefits: Comprehensive medical, dental, and vision insurance, a 401(k) plan with Cisco matching, paid parental leave, and more.
• Generous Time Off: Includes paid holidays, birthday leave, vacation, sick time, and additional time off for personal wellness and emergencies.
• Bonus and Incentive Opportunities: Annual bonuses for non-sales roles and performance-based incentives for sales roles.
• Equity Opportunities: Eligibility for Cisco restricted stock units, vesting with continued employment.
• Global Impact: Be part of a collaborative, innovation-driven culture with a worldwide network of experts.