The Artificial Intelligence / Machine Learning (AI / ML) Engineer develops AI / ML algorithms, cloud computing, and / or heterogeneous distributed computing infrastructures to support the deployment of AI / ML applications.
The AI / ML Engineer also researches the mathematical foundations and frameworks for nonlinear systems characterized by time-varying and emerging dynamics of evolving or adaptive systems.
The AI / ML Engineer develops technical solutions at the leading edge of Artificial Intelligence, Machine Learning, Genetic Programming, Computer Vision, and advanced data processing, filtering, and fusion techniques in high-performance computing and distributed heterogeneous computing environments.
The AI / ML Engineer writes parallel processing programs to deploy ML models developed by data scientists into more complex systems.
The AI / ML Engineer has familiarity with state-of-the-art, open-source software frameworks and high-performance computing accelerators for machine learning.
When conducting research, the AI / ML Engineer leverages the most recent advances in statistical analysis of large data sets to advance state-of-the-art automated sensor and data processing for a broad range of intelligent and sensor-enabled systems.
Key Responsibilities
- Apply tools and frameworks to deploy machine learning models
- Conduct data conditioning, processing, filtering, and fusion to support the creation of automated algorithms
- Make decisions regarding implementation based on available hardware (e.g., embedded systems, cloud, server infrastructure)
- Design application logging capabilities and perform debugging with available logs
Additional Responsibilities
- Develop machine learning and quantitative algorithms and methods to support cybersecurity applications
- Guide data collection and generation processes
- Research, develop and present technical presentations and documents for internal and external peer review
- Stay current on research aiming for transfer / application of techniques with well thought out technical promise and challenges
- Establish, develop, and lead novel research projects
- Lead and participate in the development of successful proposals and white papers
- Mentor junior researchers
Required Minimum Qualifications
- Experience with machine learning research and implementation
- Experience with data science
- Experience with Python (including numPy, sciPy)
- Experience with version control systems (Eg. Git)
- Demonstrated technical achievements in at least one relevant technical domain
- Excellent communication skills
- Candidates currently enrolled in an accredited degree program relevant to this position will be considered.
Preferred Qualifications
- Active Secret Clearance
- Background in computer science, mathematics, physics, informatics, or engineering field
- Experience with machine learning tools such as Tensorflow, PyTorch, and Scikit-learn
- Experience leading research projects and teams
Travel Requirements
Education and Length of Experience
This position vacancy is an open-rank announcement. The final job offer will be dependent on candidate qualifications in alignment with Research Faculty Extension Professional ranks as outlined in section of the Georgia Tech Faculty Handbook
- 2 years of related experience with a Bachelor’s degree in computer science, mathematics, physics, informatics, or engineering field
- 0 years of related experience with a Masters’ degree in computer science, mathematics, physics, informatics, or engineering field
U.S. Citizenship Requirements
Due to our research contracts with the U.S. federal government, candidates for this position must be U.S. Citizens.
Clearance Type Required
Candidates must be able to obtain and maintain an active security clearance.
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