Machine Learning Engineer - Secure AI Lab

Carnegie Mellon University•Pittsburgh, PA

9d•Onsite

About The Position

The Machine Learning Engineer will engineer solutions that support research into vulnerabilities in AI and machine learning algorithms and help secure systems against those vulnerabilities. The role is part of the Secure AI Lab in the SEI AI Division at Carnegie Mellon University, which works to improve the security and robustness of AI systems through research in counter-AI, algorithm defenses, and applied adversarial machine learning. The engineer will solve problems for government sponsors by analyzing, designing, and building responsible AI systems. Work includes investigating emerging AI technologies; defining practices, processes, and tools for AI; building prototypes; evaluating systems; and transitioning capabilities to government sponsors. The role involves collaboration with researchers, developers, designers, technical leads, and customers, as well as mentoring and sharing technical knowledge across the SEI. The position requires onsite work at the SEI offices in Pittsburgh, Pennsylvania, or Arlington, Virginia, five days per week, and travel of up to 25% to locations outside the employee’s home location. Candidates must be able to obtain and maintain an active Department of War security clearance and will be subject to a background investigation.

Requirements

A bachelor’s degree in computer science, statistics, machine learning, electrical engineering, or a related discipline and 10 years of experience; or a master’s degree in the same fields and 8 years of experience; or a PhD in a related field and 5 years of experience.
Comprehensive knowledge of machine learning.
A track record of using established engineering practices to solve difficult problems.
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 explain complex technical ideas in layperson’s terms.
Substantial experience publishing written or technical artifacts that showcase your work.
Strong collaboration skills for working with colleagues and sponsors.
Willingness to guide and mentor junior team members.
Ability to obtain and maintain an active Department of War security clearance, subject to a background investigation.
Willingness to work onsite at the SEI offices in Pittsburgh, PA, or Arlington, VA, five days per week.
Willingness to travel up to 25% of the time to locations outside the home location.

Nice To Haves

Previous experience in adversarial machine learning.

Responsibilities

Build machine learning models and systems using 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 areas including computer vision, natural language processing, planning and scheduling, robot control, and 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.
Collaborate with developers, researchers, designers, technical leads, and government customers to understand challenges, needs, and possible solutions.
Transition AI capabilities to government sponsors and provide guidance on those capabilities.
Contribute to the Division’s technical capabilities by mentoring and teaching others, participating in design sessions, and sharing knowledge across the SEI.
Identify and investigate emerging AI and AI-adjacent technologies, and define and refine processes, practices, and tools for working with AI.