Optical Engineer

Amentum•Washington, DC

2d•$123,000 - $123,000

About The Position

Purpose and Impact: The position is primarily focused on research, development, and assessment of optical sensor systems, processing schemes, and exploitation frameworks in support of U.S. Naval intelligence, surveillance, and reconnaissance (ISR) missions and Command, Control, Computer, Communications, Intelligence, Surveillance and Reconnaissance (C4ISR) goals. This includes developing and evaluating the performance of processing algorithms (e.g., target detection and identification), determining requirements, and demonstrating real-time sensor operation, on-board data processing, and exploitation techniques for ISR sensor systems. The position involves generation, documentation, and communication of research results related to sensor and target detection system performance analyses; mathematical and computer modeling and simulation; development and operation of electro-optic, infrared, hyperspectral and other multi-INT sensor and processing systems; and the design and development of automated decision-making algorithms for mapping sensor observations to actions—whereby overall research goals are to strengthen the Naval Research Enterprise and support Navy imperatives via transition of scientific and technical advances into deployed systems and platforms. Work Schedule: 9-5 Essential Responsibilities: The incumbent carries out technical management, reporting, design, development, analysis, installation, and operation of sensor systems, processing algorithms, and related computer hardware and software in coordination with the DoD, academia, and other industry partners. Other duties include development and analysis of spectral target detection and classification approaches, geo-registration schemes, sensor noise and uncertainty quantification models, atmospheric/environmental models, and lidar/radar systems and processing techniques. Additional duties include design, development, and analysis of machine learning and computer vision models supporting, for example: pattern recognition within unstructured data ensembles; automated target detection, localization, classification, segmentation, and tracking within 2D (e.g., infrared) and 3D (e.g., hyperspectral) images and video sequences; synthetic image generation; unsupervised anomaly detection; and computational image enhancement and reconstruction (e.g., de-noising, super-resolution, and sparse recovery). The incumbent must be knowledgeable in data science, computational methods, and machine learning with experience in numerical methods for the solution of inverse problems (e.g., regularized optimization frameworks), computer vision and image processing schemes, and deep learning architectures and approaches (e.g., CNNs, RNNs, GANs, autoencoders, transformers, etc.). Coding experience and proficiency in advanced technical software languages (e.g., C/C++, MATLAB, SQL, Python) and modern deep learning frameworks (e.g., TensorFlow, PyTorch, Keras) is required. The incumbent must support the execution of technical programs, interface with technology experts throughout the community, and generate documentation of research results when necessary and as appropriate for internal collaboration and external dissemination. Work Environment, Physical Demands, and Mental Demands: Work environment is primarily desk- and computer-oriented with no heavy lifting or strong mental demands.

Requirements

Ability to conceive, design, model, simulate, test, and analyze signal processing techniques for optical and active sensing systems in support of Navy surveillance, reconnaissance, and remote sensing missions and requirements.
Knowledge of various mathematical techniques, numerical methods, and algorithms relevant to signal processing and computer vision such as multi-instance segmentation and tracking in images and videos, regularized optimization frameworks for image recovery, generative adversarial networks for image synthesis, and deep learning architectures and training frameworks for processing sequential data (e.g., RNNs) and images (e.g., CNNs).
Ability to conceive and develop both offline and online real-time algorithms for signal processing and machine learning-based exploitation of multi-INT imaging sensors (e.g., panchromatic and hyperspectral) in the visible and infrared wavebands including algorithms that usefully inform decision making (e.g., multi-class object localization and recognition).
Knowledge of advanced mathematics, numerical methods, scientific programming languages (e.g., C/C++, Python, Matlab), and deep learning frameworks (e.g., PyTorch, TensorFlow, Keras).
Ability to communicate orally.
Ability to communicate in writing.
PhD
1-2

Nice To Haves

Experience with OpenCV, Pandas, NumPy, SLURM, Git, Jupyter, LaTeX, and Linux.

Responsibilities

technical management
reporting
design
development
analysis
installation
operation of sensor systems, processing algorithms, and related computer hardware and software in coordination with the DoD, academia, and other industry partners
development and analysis of spectral target detection and classification approaches, geo-registration schemes, sensor noise and uncertainty quantification models, atmospheric/environmental models, and lidar/radar systems and processing techniques
design, development, and analysis of machine learning and computer vision models supporting, for example: pattern recognition within unstructured data ensembles; automated target detection, localization, classification, segmentation, and tracking within 2D (e.g., infrared) and 3D (e.g., hyperspectral) images and video sequences; synthetic image generation; unsupervised anomaly detection; and computational image enhancement and reconstruction (e.g., de-noising, super-resolution, and sparse recovery)
support the execution of technical programs
interface with technology experts throughout the community
generate documentation of research results when necessary and as appropriate for internal collaboration and external dissemination