Applied AI Scientist

Cisco

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
Seattle, WAOklahoma City, OKNashville, TNPhoenix, AZPhiladelphia, PA
Salary
$168,000–$212,400 / yr
Posted
31 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $211k
This role $190k
$146k most similar roles pay here $276k

This role pays less than 60% of similar roles. Most pay $167,837–$254,750 — the shaded band above. At the midpoint, this role pays about $190k versus about $211k for comparable roles.

Based on 240 similar postings.

Employer

About Cisco

Cisco Systems is the world''s leading networking technology company, designing and manufacturing networking hardware, telecommunications equipment, and cybersecurity solutions for businesses and governments. Industry: Networking Technology & Cybersecurity

Cisco currently has 196 open roles on FindRole.

Listed pay typically runs $167,700–$245,200 across 196 roles with salary data.

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View all roles at Cisco

At a glance

TL;DR · Applied AI Scientist

As an Applied AI Scientist on the Foundational Modeling team, you will contribute to the research, design, and development of large-scale foundation models specifically for machine-generated data. You will focus on graph data while supporting logs, time series, traces, and event modalities to improve reliability and provide predictive insights. Your daily work involves developing distributed training and inference workflows, evaluating new AI/ML techniques, and collaborating with cross-functional teams to deliver production-ready solutions. The role requires proficiency in Python and deep learning frameworks like PyTorch or TensorFlow. You will utilize specialized tools such as PyTorch Geometric, DGL, and GraphGym to build graph neural networks and multi-modal fusion models. This position addresses the technical challenge of processing high-volume, real-time data to enhance security, observability, and infrastructure performance within complex hybrid, multi-cloud environments.

What you'll do

  • Research, design, and develop large-scale foundation models for machine-generated data including graph, log, and time-series modalities.
  • Develop and enhance distributed training and inference workflows to improve model quality, scalability, and operational efficiency.
  • Translate research ideas into production systems to address specific business and technical requirements.
  • Evaluate new AI/ML techniques and tools to solve technical challenges and support the team's roadmap.
  • Take ownership of projects by identifying obstacles and driving the resolution of technical issues.
  • Improve development processes and share technical insights with teammates to advance project outcomes.

What we're looking for

  • Master Degree in Computer Science or a related quantitative field.
  • 2+ years of industry research experience.
  • 1+ year of experience in graph representation learning, GNNs, large language modeling, or multi-modal fusion.
  • 2+ years of experience in Python and deep learning frameworks like PyTorch or TensorFlow.
  • 1+ year of experience translating research ideas into production systems.
  • Experience with specific graph frameworks such as PyTorch Geometric, DGL, GraphGym, or GraphML (preferred).
  • Expertise in constructing and operating on large-scale graphs including entity, service dependency, or log-event graphs (preferred).
  • Strong research track record with publications in top AI/ML conferences like NeurIPS, ICML, ICLR, or CVPR (preferred).

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