This role pays more than
99%
of similar roles. Most pay
$161,198–$241,750
— the shaded band above.
At the midpoint, this role pays about
$352k
versus about
$201k
for comparable roles.
Based on 240 similar postings.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
1391 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 1116 roles with salary data.
As the Senior Manager, AI Safety and Security Engineering, you will join the AI Safety & Security Engineering team to build and lead a new engineering group from its first hires. You will be responsible for hiring, coaching, and growing a founding team across harness and platform engineering, security research, and evaluation disciplines. Your daily work involves managing the Find, Validate, and Patch roadmap while collaborating with leadership in evaluation, security, and platform areas to ensure sustainable delivery. The role requires expertise in software engineering, distributed infrastructure, machine learning platforms, or security tooling. You will navigate ambiguity to define new programs while making technical trade-offs regarding architecture and evaluation in ML or systems software. This position focuses on developing AI-powered tools designed to find, validate, and patch software vulnerabilities within the critical domain of cybersecurity.
Remote (Santa Clara, CA)+423 days ago
$320,000–$488,750
Distributed Systems
ML Pipelines
LLM
Agent Frameworks
Vulnerability Research
Security Engineering
Benchmarking Infrastructure
Confidential Computing
AI Safety
Cybersecurity
Identity and Access Management
Cloud Security
Application Security
Platform Security
Security Systems Engineering
SaaS
Zero Trust
NIST CSF
NIST 800-53
ISO 27001
SOC 2
Automation
System Integration
Data Governance
Python
C#
Java
C++
C
JavaScript
Spark
Kusto
Azure Data Factory
Databricks
Kubernetes
Vector Databases
Retrieval-Augmented Generation
CI/CD
Infrastructure as Code
Data Lakes
threat-modeling