Entry-Level AI/ML Engineer for RF & Radar Tech

Lockheed Martin Corporation; Cherry Hill (VA); On-site; USD 62,000 - 116,000; Full time

Benefits offered by this job

Medical, Dental, Vision

Flexible work arrangements

401(k) match

Paid time off

Job summary

Lockheed Martin Corporation seeks an entry-level AI/ML engineer to design and apply cutting-edge ML algorithms for spectrum challenges, with end-to-end ML lifecycle experience. You will contribute to data‑driven research, scalable pipelines, and end-to-end architectures for RF and EW systems, learning from a flexible, research‑driven environment.

You will work on state-of-the-art digital/RF receivers, and participate in field tests, development of tools, and collaboration across

Qualifications

• Bachelor’s degree in EE/CE/CS/Physics from an accredited university
• 0–2 years in AI/ML research or related field
• Proficient in Python, C++, or MATLAB
• Experience with deep learning frameworks (PyTorch, TensorFlow)
• Experience with end-to-end ML lifecycle and model evaluation
• Knowledge of DevSecOps practices (CI/CD, security-by-design)
• Strong teamwork and communication
• Ability to obtain Secret-level clearance (Top-Secret preferred)

Responsibilities

• Architect and implement scalable data‑engineering pipelines for ML research over large data sets
• Design, code, and verify software for RF receivers, transmitters, and EW systems
• Support research projects with state‑of‑the‑art AI solutions
• Participate in large‑scale field tests on ground, sea, and air assets
• Assist in acquiring new business by proposing AI/ML solutions and demonstrating robustness and explainability

Skills

Python

C++

Rust

MATLAB

EDA

PyTorch

TensorFlow

Keras

CI/CD

Containerization

Data preprocessing

Security clearance

Teamwork

Education

Bachelor’s degree in EE/CE/CS/Physics

M.S. preferred

Tools

CI/CD tooling

Docker

ETL pipelines

Job description

Lockheed Martin Corporation seeks an entry-level AI/ML engineer to design and apply cutting-edge ML algorithms for spectrum challenges, with end-to-end ML lifecycle experience. You will contribute to data‑driven research, scalable pipelines, and end-to-end architectures for RF and EW systems, learning from a flexible, research‑driven environment.

You will work on state-of-the-art digital/RF receivers, and participate in field tests, development of tools, and collaboration across