Join Lockheed Martin's RMS AI team as an AI Machine Learning Engineer and help shape the integration of MLOps workflows for tactical systems. The role encompasses data curation, training and validation of AI/ML models, and supporting field deployments, with occasional travel to customer sites in Manassas, VA on a hybrid work arrangement.
Location
Manassas, Virginia, hybrid work environment.
Responsibilities
- Develop and debug an MLOps workflow integrated into a tactical system, both in the lab and at customer sites.
- Curate datasets, perform labeling, and train AI/ML models.
- Validate AI/ML algorithm results and iteratively improve performance.
- Generate datasets to support system testing and algorithm development.
- Travel to tactical sites to exercise the machine learning lifecycle, up to 25% of the time.
Requirements
- Bachelor's or Master's degree in Software Engineering, Computer Science, Machine Learning, or related STEM field.
- Experience in software development, integration, and testing.
- Familiarity with Linux.
- Active security clearance and willingness to work onsite in Manassas, VA within the advanced development lab.
Technologies
- Python
- C++
- Linux
- CUDA
- NVIDIA libraries
- Triton
- KServe
- Containers
- Cloud
Benefits
- A cutting-edge work environment equipped with state-of-the-art tools.
- Opportunity to collaborate with industry leaders and subject matter experts in Sonar and Acoustics.
- Chance to tackle highly complex, integrated subsystems engineering challenges.
- A culture that fosters creativity, excellence, and the development of remarkable products.
- Flexible schedules available, dependent on role.
Security Clearance
This position requires a government security clearance and US citizenship is required for consideration.
Clearance Level
Secret
Experience Level
Experienced Professional
Business Unit
RMS
Type
Full-Time
Schedule
4x10 hour days, three days off per week
Relocation
Possible
Remote Work
Part-time remote telework: part of the schedule may be remote and part at a Lockheed Martin facility. Weekly schedule details will be discussed during the hiring process.
Application Window
Applications close in 90 days; candidates are encouraged to apply within 5–30 days of the posting date for optimal consideration.
Locations
Locations: Nationwide & CONUS Positions
