Machine Learning Engineer - Secure AI Lab

Pittsburgh, PA

Full time

2025249

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 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.

The Secure AI 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 Secure AI 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 Secure AI Lab consists of machine learning research scientists, machine learning engineers, and software developers who work together to solve problems in the following areas:

• Counter AI Research: Study threat models targeting AI and ML algorithms, understand the behaviors of AI algorithms, identify weak points, and design novel ways to subvert AI and ML systems.

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

• Applied Adversarial Machine Learning: Advance the state of the art in adversarial machine learning by developing and transitioning capabilities to government sponsors.

As an engineer, you will solve problems for government sponsors by analyzing, designing, and building responsible AI systems.

Your day-to-day engineering tasks will include:

• 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 onAI capabilities to government sponsors.

Duties

• Building Machine Learning Models and Systems: You will work with machine learning frameworks such as TensorFlow, PyTorch, Torch, and Caffe and modern programming languages including Python, C/C++, and Java. You will build and work with data pipelines, ETL processes, and backend systems. You will work with, extend, and implement state-of-the-art machine learning methods.

• Technical Experimentation: You will experiment with modern and emerging machine learning frameworks, methods, and algorithms in application domains that include computer vision, natural language processing, planning and scheduling, robot control, and engineering safe, trusted, and reliable machine learning systems.

• Testing and evaluation. You'll conduct rapid prototyping to demonstrate and evaluate technologies in relevant environments. You'll evaluate systems for performance and security. You'll test capabilities using novel testing and analysis techniques.

• Collaboration. You'll actively participate on teams of developers, researchers, designers, and technical leads. You'll collaborate with researchers and our government customers to understand challenges, needs, and possible solutions.

• Mentoring. You'll contribute to improving the overall technical capabilities of the Division by mentoring and teaching others, participating in design (software and otherwise) sessions, and sharing insights and wisdom across the SEI.

Knowledge and Experience

• 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

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 an active Department of War security clearance.

• You must be willing to work onsite at the SEI's offices in Pittsburgh, PA or Arlington, VA 5 days per week.

• Willing to travel up to 25% of the time to locations outside of your home location.

Joining the CMU team opens the door to an array of exceptional benefits.

Benefits eligible (https://www.cmu.edu/hr/benefits/eligibility/index.html) employees enjoy a wide array of benefits including comprehensive medical, prescription, dental, and vision insurance (https://www.cmu.edu/hr/benefits/health-welfare/index.html) as well as a generous retirement savings program (https://www.cmu.edu/hr/benefits/retirement-savings/index.html) with employer contributions. Unlock your potential with tuition benefits (https://www.cmu.edu/hr/benefits/tuition/index.html) , take well-deserved breaks with ample paid time off (https://www.cmu.edu/hr/benefits/time-away/pto.html) and observed holidays (https://www.cmu.edu/hr/benefits/time-away/holidays.html) , and rest easy with life and accidental death and disability insurance.

Additional perks include a free Pittsburgh Regional Transit bus pass, access to our Family Concierge Team (https://www.cmu.edu/hr/work-life/support/family-child-care-resources/index.html) to help navigate childcare needs, fitness center access (https://athletics.cmu.edu/recreation/facilities) , and much more!

For a comprehensive overview of the benefits available, explore our Benefits page (https://www.cmu.edu/hr/benefits/index.html) .

At Carnegie Mellon, we value the whole package when extending offers of employment. Beyond credentials, we evaluate the role and responsibilities, your valuable work experience, and the knowledge gained through education and training. We appreciate your unique skills and the perspective you bring. Your journey with us is about more than just a job; it’s about finding the perfect fit for your professional growth and personal aspirations.

Are you interested in an exciting opportunity with an exceptional organization?! Apply today!

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 (http://www.cmu.edu/jobs/why-cmu/index.html) ” to learn more about becoming part of an institution inspiring innovations that change the world.

• Click here (https://www.cmu.edu/jobs/benefits-at-a-glance/) to view a listing of employee benefits

• Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran .

• Statement of Assurance (https://www.cmu.edu/policies/administrative-and-governance/statement-of-assurance.html)

Interested in a career with Carnegie Mellon University but not finding anything that currently aligns with your interests, background, or experience? Learn how to sign up for Job Alerts (https://www.cmu.edu/jobs/external-applicants.html#job-alerts) through your candidate profile.

If your heart is in your work, come work with us. Carnegie Mellon University isn’t just one of the world’s most renowned educational institutions – it’s also a hotspot for some of the most talented doers, dreamers, and difference-makers on the planet. When you join our staff, you’ll become an important part of our mission to create a healthier, safer, and more just life for all. No matter what your role or location, you’ll connect and collaborate with dedicated, passionate colleagues – and you’ll have the satisfaction of delivering work that truly matters.

We cultivate a vibrant, welcoming environment where everyone is valued and encouraged to contribute and achieve. In addition to competitive benefits and a robust support network, you’ll have access to many tools and resources to sharpen your abilities and professional skills, as well as opportunities to engage and share perspectives with a dynamic and inspiring community of uniquely talented staff, faculty, students, and alumni.

The future is awaiting your expertise and intellect. Come join the architects of what’s next. Apply now.

Learn more about Student Employment (https://www.cmu.edu/sfs/student-employment/index.html) .

Please see Faculty Careers. (https://www.cmu.edu/faculty-office/faculty-recruitment/faculty-careers.html)

For technical assistance, email HR Services ([email protected]) or call 412-268-4600.

We are committed to providing an accessible experience throughout our recruitment process. If you need assistance or a reasonable accommodation at any stage of the application, interview, or hiring process, please contact Equal Opportunity Services by email at [email protected] or by phone at 412-268-5072.

Prospective Employee Disclosures (https://www.cmu.edu/jobs/disclosures/index.html)