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AI and ML Architect

Company: mLogica
Location: White Plains
Posted on: September 10, 2019

Job Description:

Opportunity Summary: This program will consist of two primary tasks. Both tasks will concentrate on prototype development and evaluation for a single domain; however, there is a distinction between the two.

  • Task 1 is focused on rapid prototype development for AI/ML applications supporting the operational C2 tools and processes. Due to the criticality of this task, several efforts will be spun up as quickly as possible to address as many operational challenges as resources permit, with each Offeror responsible for the evaluation of their solutions.
  • Task 1 will also contain an optional task to extend the original workflow to multi-domain use-case(s) with a scaled-down number of solutions.
  • Task 2 is specifically focused on applying RL to air combat and mobility operational-level planning processes, such as the development of ATOs, COAs, Airlift Schedules, Master Air Attack Plans (MAAP), and complex mission packages.
    • In addition to algorithmic prototype development, the objective of Task 2 also includes the design of a necessary supporting simulation and evaluation environment for training and execution of AI/ML algorithms for C2 planning. The intent of this supporting development and evaluation environment is to emulate the environment and to provide feedback to the ML algorithm being trained at speed (time to evaluate plan), scale (size of the campaign), and fidelity (level of detail). Both tasks are subject to the challenges of data representation mentioned in the previous section. However, the reliance on RL algorithms for Task 2 introduces additional challenges alluded to earlier and covered in detail under the respective task description, and it is anticipated that only one award will be made under this Task. The potential high-impact areas for AI/ML enhancements are listed below in Table 1 as eight operational challenges that are denoted in the shaded boxes. Each of the eight operational threads are further defined in accompanying Appendix document. Performers may also propose their own operational thread and candidate AI/ML solutions that are outside the shaded areas but must also provide an accompanying description equivalent to those eight defined in the accompanying Appendix document. - provided by Dice

Keywords: mLogica, White Plains , AI and ML Architect, Professions , White Plains, New York

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