Company

Carnegie Mellon UniversitySee more

addressAddressUnited, PA
CategoryEducation/Training

Job description

Description

At the SEI AI Division, we conduct research in applied artificial intelligence and the engineering questions related to the practical design and implementation of AI technologies and systems.

We currently lead a community-wide movement to mature the discipline of AI Engineering for Defense and National Security.
As our government customers adopt AI and machine learning to provide leap-ahead mission capabilities, we
  • build real-world, mission-scale AI capabilities through solving practical engineering problems
  • discover and define the processes, practices, and tools to support operationalizing AI for robust, secure, scalable, and human-centered mission capabilities
  • prepare our customers to be ready for the unique challenges of adopting, deploying, using, and maintaining AI capabilities
  • identify and investigate emerging AI and AI-adjacent technologies that are rapidly transforming the technology landscape


Are you creative, curious, energetic, collaborative, technology-focused, and hard-working? Are you interested in making a difference by bringing innovation to government organizations and beyond? Apply to join our team.


Overview:
As a Senior Machine Learning Research Scientist, you will specialize in conducting adversarial machine learning (AML) research.
The AML Lab within the SEI's AI Division focuses on improving the security and robustness of AI systems.

As part of the world-class research community at Carnegie Mellon University, the AML Lab conducts and applies cutting-edge research to protect AI systems from adversaries who aim to manipulate the system to learn, do, or reveal something it isn't supposed to.

The AML Lab consists of machine learning Research Scientists, machine learning engineers, and software developers who work together to solve problems in the following areas:
  • AI/ML

Algorithm Attack Research:
Study threat models targeting AI/ML algorithms, identify weak points, and design novel ways to subvert AI/ML systems.
  • AI/ML

Algorithm Defense Research:
Create practical mitigations and defenses for observed attacks affecting AI/ML algorithms and evaluate the effectiveness of defensive techniques.
  • Applied

AML:
Advance the state of the art in adversarial machine learning by developing and transitioning capabilities to government sponsors.
Your day-to-day research tasks will include:
  • Identifying and investigating emerging AI and AI-adjacent technologies.
  • Performing and publishing impactful original research in the field of adversarial machine learning.
  • Adapting and applying existing research in the field to solve real-world problems.
  • Transitioning and providing guidance on AI capabilities to government sponsors.

Duties:
  • Hands-on research: You'll conduct and lead novel research in applied machine learning and artificial intelligence.
  • Solution development: You'll work with and lead interdisciplinary teams to turn research results into prototype operational capabilities for government customers and stakeholders.
  • Strategy: You'll work with the leadership team and colleagues to plan, develop, and carry out an overall research strategy, and to influence the national research agenda regarding future technology.
  • Collaboration: You'll actively participate on teams of software developers, researchers, designers, and technical leads. You'll build relationships and collaborate with researchers, government customers, and other stakeholders to understand challenges, needs, possible solutions, and research directions.
  • Mentoring: You'll contribute to improving the overall technical capabilities of the Center by mentoring and teaching others, participating in design (software and otherwise) sessions, and sharing insights and wisdom across the SEI AI Division.
Knowledge and Experience
  • Comprehensive knowledge of machine learning; previous experience in adversarial machine learning preferred
  • A track record of conducting research and applying scientific methods to solve difficult problems
  • Experience leading research projects in novel areas with limited previous work to build upon
  • Ability to work with leadership to plan, develop, and deliver an overall research strategy
  • Strong written and verbal communication skills; ability to convey complex technical ideas in a layperson's terms
  • Proficiency in writing funding proposals or pitching ideas for new research projects
  • Ample experience with publishing written or technical artifacts showcasing your work
  • Strong collaboration skills for working with colleagues and sponsors
  • Willingness to guide and mentor junior team members
  • An active TS/SCI clearance is strongly preferred.
Requirements
  • A bachelor's degree in computer science, statistics, machine learning, electrical engineering, or related discipline with ten (10) years of experience; OR MS in the same fields with eight (8) years of experience; OR PhD in with five (5) years of experience
  • You will be subject to a background investigation and must be able to obtain and maintain a Department of Defense TS/SCI security clearance.
  • Legally authorized to work for Carnegie Mellon University in the United States. CMU will not sponsor or take over sponsorship of an employment visa for this opportunity.
  • Willing to travel up to 25% of the time to locations outside of your home location. Travel sites include SEI offices in Pittsburgh and Washington, D.C., sponsor sites, and conferences.
Location
Pittsburgh, PA
Job Function
Software/Applications Development/Engineering
Position Type
Staff – Regular
Full Time/Part time
Full time
Pay Basis
Salary
More Information:


Please visit "Why Carnegie Mellon" to learn more about becoming part of an institution inspiring innovations that change the world.

Click here to view a listing of employee benefits
Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran.
Statement of Assurance
Refer code: 8280774. Carnegie Mellon University - The previous day - 2024-02-21 12:53

Carnegie Mellon University

United, PA
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