Standard Job Description

We are seeking an emerging A/AI Research Engineer who will join a highly skilled team of systems engineering technologists and algorithm developers supporting various contracts and IRADs within Missiles and Fire Control.  The engineer focuses on research & development of technologies that enable and advance semi and fully autonomous systems for both defense and commercial customers. Serves as the algorithm expert with up-to-date knowledge on modern AI research and may be involved in the inception of ideas and drive the development cycles from research to test of prototypes for a major project or component of a major project. Researches and discovers improvements to machine learning and robotic algorithms; Drives advancements in techniques used in signal processing, computer vision (CV), and control systems; Develops AI algorithms for mission systems; Applies latest research on AI algorithms and trains machine learning / deep learning models to solve a variety of problems; Investigates and applies the latest machine learning and deep learning techniques; Optimizes the performance of AI algorithms, applications, and platforms; Develops and documents algorithm and implementation requirements; Develops prototypes that will enable autonomous functionality in LM products and platforms; Interfaces with other teams involved the development lifecycle for perception, mission and motion planning, simulation and modeling, testing, etc.

The typical Assc. AI-ML Engineer should show:

• KNOWLEDGE - Demonstrates basic understanding and applies fundamental concepts within area of specialization.
• COMPLEXITY - Exercises judgement and problem-solving skills to independently complete assignments.
• IMPACT - Completes assignments requiring judgment and discretion.

Typical tasks may include: 

• Implement and test deep learning object detection and classification solutions and image processing and augmentation methods for missile and fire control products
• Validate and test complex models and simulations that utilize convolutional neural networks, transformers, generative AI, and other such techniques to detect and classify objects of interest.
• Deploy AI/ML algorithms to CPUs, GPUs or edge devices
• Evaluate system performance in complex scenarios and environments and verify system and subsystem level requirements
• Perform test activities that support ground and flight test efforts including Hardware-In-The-Loop (HWIL) activities
• Support program reviews and technical interchange meetings with internal leadership and/or external customers

Basic Qualifications

• BS in electrical engineering, computer engineering, physics, computer science, applied mathematics, or similar STEM degree.
• Interim Clearance is needed to start, therefore you must be a US Citizen.
• Should be proficient in one or more of the following languages:

• MATLAB, python, C++

• Should demonstrate the ability to perform one or more of the following Image Processing (IP) assignments based on completed course work or professional experience:

• Train and inference on modern deep learning neural networks for object detection, classification, and be able to analyze and interpret results.

• Should demonstrate strong math skills in the areas of:

• Linear algebra, matrix math, statistics, trigonometry, and convolution transformations

Desired Skills

• Active Secret Clearance
• Experience developing and analyzing algorithms related to computer vision
• Experience designing and analyzing object detection and classification networks and applying image augmentation and explainable AI
• Demonstrated skills in probability, statistics, and Design of Experiments (DOE)
• Experience deploying algorithms that satisfy real-time performance requirement to various hardware platforms
• Experience in validating C++ algorithm simulations and hardware models with real-time data collections
• Have been exposed to implementing and debugging AI_ML algorithms running in a real-time processing environments
• Ability to perform preflight system performance assessment and post flight verification analyses