Advance scientific discovery and technology transition in human systems, robotics and autonomy, spectrum systems, data analytics and more for Lockheed Martin
Requirements
- AI/ML engineering skills
- Data engineering pipeline architecture and implementation skills
- Cognitive software and systems design, coding and testing skills
- Machine learning, sensor processing, and target tracking research prototype development skills
- DevSecOps fundamentals
- RF processing and target tracking software development skills
Responsibilities
- Architecting and implementing data engineering pipelines in support of automated analysis of machine learning, sensor processing, and target tracking research prototypes over large data sets
- Designing, coding and testing of cognitive software and systems for digital and RF/analog advanced state-of-the-art receivers, transmitters, antennas, and jam and anti-jam systems
- Lead and/or support research projects to innovate and provide novel state of the art solutions in areas such as parameter estimation, reinforcement learning, and generative AI
- Design, code and test of software for digital and RF/analog advanced state-of-the-art receivers, transmitters, antennas, and jam and anti-jam systems
- Architect and implement data engineering pipelines in support of automated analysis of machine learning, sensor processing, and target tracking research prototypes over large data sets
- Utilize DevSecOps fundamentals to analyze, debug, and integrate RF processing and target tracking software
- Enable acquisition of new business by developing modern day solutions to customer problems
Other
- Support research and technology development projects funded by DARPA, DOD service labs such as AFRL, and internal R&D
- Lead small teams to develop advanced wireless communication systems, RADAR systems, Electronic Warfare systems, and advanced algorithm design
- Attend and present at various industry conferences and customer venues
- Assist in the acquisition of new business through proposing modern-day solutions to our customer’s problems and advocating for the robustness, explainability, and generalizability of AI/ML solutions
