As an Applied Researcher II on the cutting-edge AI team, you will lead innovative projects focusing on geometric deep learning and adversarial machine learning. Your daily tasks include developing scalable graph neural networks and sequential models, contributing to large-scale recommender systems, and ensuring robustness against security threats in real-time environments. Preferred qualifications include a PhD with expertise in Graph Neural Networks, Sequential Models, and Multivariate Time Series, along with experience scaling these models to over 50 million nodes and working on datasets with 100 million users. You should also have contributions to open-source frameworks like PyTorch-Geometric and DGL, and a track record of publishing in top-tier conferences such as KDD, ICML, NeurIPS, and ICLR. Additionally, deep knowledge in adversarial machine learning, model alignment, and AI safety is crucial for addressing real-world deployment challenges.
Skills
Python
PyTorch
DGL
pytorch-geometric
Graph Neural Networks
Sequential Models
Multivariate Time Series
KDD
ICML
NeurIPS
ICLR
Deep Learning
Recommender Systems
Real-time Streaming
Adversarial Machine Learning
Prompt Injection
Model Inversion
RAG Poisoning
AI Explainability
CI/CD
What you'll do
Conduct advanced research in geometric deep learning and sequential models.
Develop and scale graph neural networks to handle datasets with over 50 million nodes.
Create large-scale deep learning recommender systems for real-time applications.
Contribute to open-source frameworks like PyTorch Geometric and DGL.
Propose new methods for inference or representation learning on graphs and sequences.
Perform adversarial machine learning research to identify novel attack surfaces.
What we're looking for
PhD in a relevant field with focus on geometric deep learning or adversarial machine learning.
Published multiple papers at KDD, ICML, NeurIPS, ICLR on graph and sequential data models.
Experience scaling graph models to over 50 million nodes and working with large-scale recommender systems.
Expertise in production real-time environments and contributions to open-source frameworks like PyTorch Geometric or DGL.
Conducted foundational research in AI safety, including developing scalable evaluation suites for adversarial threats.
Market check
Salary context
This
$262,500–$299,600
range sits above
95%
of similar postings on FindRole.
Peer median band
$115,900–$220,000
Median floor and ceiling across peers.
Typical midpoint (25–75%)
$130,787–$201,700
Middle half of comparable postings.
Based on 240 comparable postings.*
* 240 is the maximum number of comparable postings sampled.
Employer
About Capital One Financial
Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking
Capital One Financial currently has
489 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 483 roles with salary data.