Alion Science and Technology is seeking an Intern for a temporary, part time position who will perform advanced artificial intelligence (AI) research and development (R&D) as part of a research team, in support of one or more of a wide array of application areas, including autonomy, sensor augmentation/computer vision, virtual opponents for military training, natural language processing, cyberdefense/cybersecurity, and command decision support.
This position seeks current undergraduate or graduate students with skills and experience in AI-related fields (see Knowledge, Skills, and Abilities below).
Duties and Responsibilities:
Education and Experience:
- Research state-of-the-art algorithms in machine learning, particularly deep learning, to identify viable approaches to significant unsolved challenges for Alion’s clients.
- Design solution prototypes that connect data sources through the selected algorithms to a concrete use case.
- Develop code to implement the algorithms, and test their efficacy and efficiency against real-world data.
- Deploy the solution in a production environment, if appropriate to the specific project, in collaboration with the relevant Alion team and client.
Must have a high school diploma or GED and must be enrolled in a degree-granting program at an accredited public or private college or university.
Knowledge, Skills, and Abilities:
- Proficiency in the underlying mathematics of deep learning, particularly linear algebra and multivariate calculus.
- Knowledge of data structures and data management methods, and the ability to analyze a problem and determine an efficient structure for the task.
- Ability to communicate technical topics effectively to both technical and nontechnical audiences.
- Ability to read, understand, and apply technical papers and articles in research journals.
- Ability to work independently and collaborate effectively with a project team in a research environment.
- A proactive and curious problem-solving approach. Ability to obtain a security clearance after employment.
- A successful project in machine learning, particularly deep learning, that demonstrates the ability to create and train end-to-end solutions combining data preparation, advanced analysis, and useful outputs.
- Experience with deep learning frameworks and libraries, particularly TensorFlow, Keras, Caffe, or Torch.
- Experience with Jupyter notebooks or NVIDIA DIGITS.
- Familiarity with probability theory, computational complexity theory, and optimization theory.
- Experience using NVIDIA GPUs for deep learning training, particularly cuDNN.
- Experience with cloud computing and storage services, including Amazon Web Services (AWS), Microsoft Azure, or Google Cloud; specific experience with machine learning and deep learning capabilities on those platforms is preferred.
- Experience with containerization technologies, particularly Docker and Kubernetes.
- Experience with web technologies for human-machine interfaces or experience with lower-level programming for embedded systems.