Machine Learning researchers at the SEI help our government and industry clients solve their problems using ML technology. In this role, you will work with our customers to identify areas where advanced statistical techniques can help tackle problems, plan and develop prototype solutions, and build out final products. You'll get a chance to work with elite cybersecurity professionals and university faculty to build new technologies that will influence national cybersecurity strategy for decades to come. You will co-author research proposals, execute studies, and present findings to DoD sponsors and at academic conferences.
Our team works on a wide range of projects. Some of our current work includes developing metrics and experimental designs for large-scale cybersecurity research programs, researching human-in-the-loop machine learning, and building classifiers to identify security vulnerabilities in code. We have access to a wide variety of cyber-related data, including malware samples, netflow data, cybersecurity training runs and tests, incident tickets, and more. If you are a computer science or statistics expert with an interest in cybersecurity, we want to hear from you!
- BS in machine learning, cybersecurity, statistics, or related discipline or equivalent combination of training or experience.
- Willingness to travel to various locations to support the SEI’s overall mission. This includes within the SEI and CMU community, sponsor sites, conferences, and offsite meetings on occasion (5%).
- You will be subject to a background check and will need to obtain and maintain a Department of Defense security clearance.
Knowledge, Skills and Abilities:
- Experience with Natural Language Processing, Neural Networks, Optimization Theory, Graph Theory, or Computer Vision
- Expertise implementing and applying machine learning techniques to different data sets
- Familiar with at least one mathematical/statistical programming package (e.g., python numpy/scipy/pandas, R, MATLAB, etc.)
- Comfortable working in the Unix command line
- Familiar with at least one deep learning framework (e.g., TensorFlow, Caffe)
- Expertise implementing machine learning techniques (e.g., K-means, SVM, neural networks)
- Superb communication skills (oral and written), particularly regarding technical communications with non-experts
- Deep understanding of statistical modeling techniques
- Strong software engineering skills
- Cybersecurity or Privacy experience
- Experience with project management
Please visit “Why Carnegie Mellon” to learn more about becoming part of an institution inspiring innovations that change the world.
A listing of employee benefits is available at: www.cmu.edu/jobs/benefits-at-a-glance/.
Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran.