Overview
On Site
USD 67.00 per hour
Full Time
Skills
Embedded Systems
Research and Development
Privacy
Real-time
Authorization
SAFE
Usability
Workflow
Regression Analysis
Auditing
Stress Testing
Open Source
Computer Science
Orchestration
Evaluation
Python
PyTorch
TensorFlow
Research
Prototyping
Publications
Machine Learning (ML)
Artificial Intelligence
OAuth
OIDC
Oracle Policy Automation
Program Evaluation
Conflict Resolution
Problem Solving
Communication
Law
Legal
Collaboration
Job Details
We're looking for PhD candidates to intern on the AI Security team during winter 2026 (12 weeks). You will be embedded in our engineering team and work closely with other specialists, software developers, and product managers. As a PhD intern, you will contribute to research and development of AI agents for security and privacy. You'll explore methods to build, evaluate, and scale agents that can reason about complex systems, detect vulnerabilities, propose and apply patches, and verify security outcomes.
About the Team
Uber's AI Security team secures how AI agents and tools interact with our systems and data. We build the foundations for agentic identity (who the agent is, what it's acting on behalf of, and how identity/attestation propagates across tools) and risk-based access (context-aware, real-time authorization that adapts to sensitivity, intent, and behavior). We partner across EngSec, Edge Gateway, Developer Platform, and ML Platform teams to make AI adoption safe, observable, and compliant at Uber scale.
What You'll Do
- Research & prototype identity and attestation for AI agents (e.g., A2A AuthN/A2A AuthZ, context propagation, chain-of-custody verification) and evaluate correctness, robustness, and usability
- Design risk-based access policies and scoring that adapt to actor, tool, data sensitivity, and runtime signals; validate via offline/online experiments
- Build evaluation harnesses for agent workflows (tool-use, multi-step planning, self-verification) to measure security outcomes (prevent, detect, contain) and regression-proof changes
- Ship with engineers: integrate prototypes into production gateways/SDKs; add observability (auditing, explanations of allow/deny), and stress-test for scale and latency
- Communicate findings through docs, internal talks, and (where appropriate) publications or open-source contributions
Basic Qualifications
- Current PhD student in Computer Science, AI/ML, Security, or related field
- Candidates must have at least one semester/quarter of their education left following the internship
- Strong grounding in LLMs/agent frameworks (tool use, planning, orchestration) and empirical evaluation
- Proficiency in Python and modern ML tooling (PyTorch or TensorFlow)
- Demonstrated ability to conduct independent research and translate ideas into working prototypes
Preferred Qualifications
- Publications in top ML/AI or Security venues (e.g., NeurIPS, ICML, ICLR, USENIX Security, CCS, IEEE S&P)
- Experience with identity/authz standards (OAuth2/OIDC), policy engines (e.g., OPA/Rego), or program analysis/verification
- Applied security for LLM/agent systems (prompt/ tool security, redaction, auditability, explainability)
- Strong problem-solving and communication; comfort navigating ambiguous, cross-functional spaces
For New York, NY-based roles: The base hourly rate amount for this role is USD$67.00 per hour.
For San Francisco, CA-based roles: The base hourly rate amount for this role is USD$67.00 per hour.
For Seattle, WA-based roles: The base hourly rate amount for this role is USD$67.00 per hour.
For Sunnyvale, CA-based roles: The base hourly rate amount for this role is USD$67.00 per hour.
For all US locations, you will also be eligible for various benefits.
Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](;br>
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
About the Team
Uber's AI Security team secures how AI agents and tools interact with our systems and data. We build the foundations for agentic identity (who the agent is, what it's acting on behalf of, and how identity/attestation propagates across tools) and risk-based access (context-aware, real-time authorization that adapts to sensitivity, intent, and behavior). We partner across EngSec, Edge Gateway, Developer Platform, and ML Platform teams to make AI adoption safe, observable, and compliant at Uber scale.
What You'll Do
- Research & prototype identity and attestation for AI agents (e.g., A2A AuthN/A2A AuthZ, context propagation, chain-of-custody verification) and evaluate correctness, robustness, and usability
- Design risk-based access policies and scoring that adapt to actor, tool, data sensitivity, and runtime signals; validate via offline/online experiments
- Build evaluation harnesses for agent workflows (tool-use, multi-step planning, self-verification) to measure security outcomes (prevent, detect, contain) and regression-proof changes
- Ship with engineers: integrate prototypes into production gateways/SDKs; add observability (auditing, explanations of allow/deny), and stress-test for scale and latency
- Communicate findings through docs, internal talks, and (where appropriate) publications or open-source contributions
Basic Qualifications
- Current PhD student in Computer Science, AI/ML, Security, or related field
- Candidates must have at least one semester/quarter of their education left following the internship
- Strong grounding in LLMs/agent frameworks (tool use, planning, orchestration) and empirical evaluation
- Proficiency in Python and modern ML tooling (PyTorch or TensorFlow)
- Demonstrated ability to conduct independent research and translate ideas into working prototypes
Preferred Qualifications
- Publications in top ML/AI or Security venues (e.g., NeurIPS, ICML, ICLR, USENIX Security, CCS, IEEE S&P)
- Experience with identity/authz standards (OAuth2/OIDC), policy engines (e.g., OPA/Rego), or program analysis/verification
- Applied security for LLM/agent systems (prompt/ tool security, redaction, auditability, explainability)
- Strong problem-solving and communication; comfort navigating ambiguous, cross-functional spaces
For New York, NY-based roles: The base hourly rate amount for this role is USD$67.00 per hour.
For San Francisco, CA-based roles: The base hourly rate amount for this role is USD$67.00 per hour.
For Seattle, WA-based roles: The base hourly rate amount for this role is USD$67.00 per hour.
For Sunnyvale, CA-based roles: The base hourly rate amount for this role is USD$67.00 per hour.
For all US locations, you will also be eligible for various benefits.
Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](;br>
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.