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Carnegie Mellon University

University training problem solvers and innovators

Machine Learning Engineer - Secure AI Lab

Applied Machine LearningUpdated on Nov 14
Full-timeNo salary listed

About the Job

Requirements

  • Comprehensive knowledge of machine learning; previous experience in adversarial machine learning is desirable but not required.
  • A track record of using well-established engineering practices to solve difficult problems.
  • An understanding of how to convert research results into functioning prototypes or capabilities.
  • Experience leading technical projects in novel areas with limited previous work to build upon.
  • Strong written and verbal communication skills, including the ability to convey complex technical ideas in layperson’s terms.
  • Ample experience publishing written or technical artifacts showcasing the candidate’s work.
  • Strong collaboration skills for working with colleagues and sponsors.
  • Willingness to guide and mentor junior team members.
  • A bachelor's degree in computer science, statistics, machine learning, electrical engineering, or a related discipline with eight years of experience; or an MS in the same fields with five years of experience; or a PhD with two years of experience.
  • Must be able to obtain and maintain an active Department of War security clearance.
  • Must be willing to work onsite at the SEI's offices in Pittsburgh, Pennsylvania, or Arlington, Virginia, five days per week.
  • Willingness to travel up to 25% of the time to locations outside the home location.

Responsibilities

  • Specialize in engineering solutions that support research into vulnerabilities of AI and machine learning algorithms and securing against those vulnerabilities.
  • Identify and investigate emerging AI and AI-adjacent technologies.
  • Define and refine processes, practices, and tools for working with AI.
  • Design and build well-engineered prototypes of AI systems.
  • Transition AI capabilities to government sponsors and provide guidance on those capabilities.
  • Build machine learning models and systems using machine learning frameworks such as TensorFlow, PyTorch, Torch, and Caffe, and programming languages including Python, C/C++, and Java.
  • Build and work with data pipelines, ETL processes, and backend systems.
  • Work with, extend, and implement state-of-the-art machine learning methods.
  • Experiment with modern and emerging machine learning frameworks, methods, and algorithms in application domains including computer vision, natural language processing, planning and scheduling, robot control, and engineering safe, trusted, and reliable machine learning systems.
  • Conduct rapid prototyping to demonstrate and evaluate technologies in relevant environments.
  • Evaluate systems for performance and security, and test capabilities using novel testing and analysis techniques.
  • Participate on teams of developers, researchers, designers, and technical leads.
  • Collaborate with researchers and government customers to understand challenges, needs, and possible solutions.
  • Improve the Division's technical capabilities by mentoring and teaching others, participating in software and other design sessions, and sharing insights across the SEI.

Desired Qualifications

  • Previous experience in adversarial machine learning.

About the Company

Carnegie Mellon University

University training problem solvers and innovators

What Carnegie Mellon University does: It provides higher education and research across a wide range of fields, especially technology, engineering, sciences, and the arts, helping students become ready to enter the workforce and pursue innovative work. How its products work: It offers degree programs (bachelor’s, master’s, doctoral) and professional schools where students learn through classes, labs, projects, research opportunities, and collaborations with industry and the community. How it differentiates from competitors: CMU combines strong strengths in STEM with arts and design, interdisciplinary programs, and active collaboration with industry partners, all supported by a culture that emphasizes hands-on problem solving and real-world impact. What the goal is: To train capable graduates who can solve real problems, drive innovation, and contribute to technology, the arts, and society in meaningful ways.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Pittsburgh, PA
Founded
2018

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