Machine Learning Engineer focusing on vulnerabilities and security of AI systems at Carnegie Mellon University. Collaborating with a team to build robust prototypes and provide solutions for government sponsors.
Responsibilities
As an Machine Learning Engineer, you will specialize in engineering solutions that support research into the vulnerabilities of AI and ML algorithms and securing against those vulnerabilities.
You will solve problems for government sponsors by analyzing, designing, and building responsible AI systems.
Identifying and investigating emerging AI and AI-adjacent technologies.
Defining and refining processes, practices, and tools for working with AI.
Designing and building well-engineered prototypes of AI systems.
Transitioning and providing guidance on AI capabilities to government sponsors.
Building Machine Learning Models and Systems using frameworks such as TensorFlow, PyTorch, Torch, and Caffe.
You will build and work with data pipelines, ETL processes, and backend systems.
Conducting rapid prototyping to demonstrate and evaluate technologies in relevant environments and assessing systems for performance and security.
Actively participating on teams of developers, researchers, designers, and technical leads to address challenges and propose solutions.
Contributing to improving the overall technical capabilities of the Division by mentoring and teaching others.
Requirements
A bachelor’s degree in computer science, statistics, machine learning, electrical engineering, or related discipline with eight (8) years of experience; OR MS in the same fields with one (1) year of experience; OR PhD in a relevant discipline with two (2) years of experience.
Willingness to work onsite 5 days per week at SEI offices in Pittsburgh, PA or Arlington, VA.
You will be subject to a background investigation and must be able to obtain and maintain an active Department of War security clearance.
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.
Comprehensive knowledge of machine learning; previous experience in adversarial machine learning 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; able to convey complex technical ideas in a layperson’s terms.
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.
Benefits
Comprehensive medical, prescription, dental, and vision insurance
Generous retirement savings program with employer contributions
Tuition benefits
Ample paid time off and observed holidays
Life and accidental death and disability insurance
Free Pittsburgh Regional Transit bus pass
Access to Family Concierge Team to help navigate childcare needs
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