A/AI Research Engineer - E2
Lockheed Martin
- Location
- Orlando, FL
- Work model
- On-Site
- Level
- Entry
- Posted
- 1h ago
Skills
About this role
Standard Job Description We are seeking an experienced 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 AI_ML Engineer should show: KNOWLEDGE - Demonstrates a strong understanding and applies industry techniques within area of specialization. COMPLEXITY - Develops solutions to problems of moderate scope and complexity. IMPACT - Contributes to organizational projects and goals. Represents on specific projects and teams, contributing to effective collaboration and problem resolution. Typical tasks may include: Develop, test, and verify deep learning object detection and classification solutions and image processing and augmentation methods for missile and fire control products Develop, 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. Develop, validate and deploy AI/ML algorithms to CPUs, GPUs or edge devices Evaluate and analyze system performance in complex scenarios and environments and verify system and subsystem level requirements Perform analyses and test activities that support ground and flight test efforts including Hardware-In-The-Loop (HWIL) activities Opportunities will exist to join small teams of engineers and algorithm developers on a variety of different programs that are in various stages of product development. Support program reviews and technical interchange meetings with internal leadership and/or external customers Basic Qualifications BS in electrical engineering, mechanical engineering, aerospace engineering, physics, computer science, applied mathematics, or similar STEM degree and 1+ years of relevant experience. Interim Clearance is needed to start, therefore you must be a US Citizen. Shall be fluent in one or more of the following languages: MATLAB, python, C++ Shall have experience solving problems and relevant algorithm development in the AI_ML domains mentioned below: Experience in training and inference on modern deep learning neural networks for object detection, classification, and be able to analyze and interpret results. Experience designing and analyzing object detection and classification networks and applying image augmentation and explainable AI Experience in using deep learning frameworks such as: PyTorch, TensorFlow, ONNX Experience deploying neural networks on embedded/edge devices Understanding of how to design neural network architectures and their computational requirements and impacts Shall demonstrate strong math skills in the areas of: Linear algebra, matrix math,