eightfold
Associate AI/ML Engineer
Lockheed Martin
New Jersey, USA
Full-time
Entry
Hybrid
Discovered Yesterday
Free
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Standard Job Description
Spectrum Systems Lab (SSL) is seeking an entry‑level AI/ML engineer with the flexibility to incorporate and apply cutting‑edge research to a variety of problems.
As an engineer on our SSL team, you will have the opportunity to design new algorithms and toolsets to address spectrum challenges, augment existing solutions with data‑driven ML approaches, and integrate best‑practice ML operations into an end‑to‑end architecture for our customers and stakeholders.
We pride ourselves on the flexibility we give our engineers to pursue research that interests them and on providing opportunities for engineers to grow and learn about what others in the lab are doing.
Potential tasking includes:
- Architect and implement scalable data‑engineering pipelines for automated analysis of machine‑learning, sensor‑processing, and target‑tracking research prototypes over large data sets
- Design, code, and verify cognitive software and systems for state‑of‑the‑art digital/RF receivers, transmitters, and EW systems
- Support research projects to innovate and provide novel state of the art solutions in areas such as parameter estimation, reinforcement learning, and generative AI
- Participate in large‑scale field tests on ground, sea, and air assets, assisting with system deployment, data collection, and post‑test analysis
- 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
Basic Qualifications
- Education – Bachelor’s degree (M.S. preferred) from an accredited university in Electrical Engineering, Computer Engineering, Computer Science, Physics, or a closely related field
- Early‑career experience (0‑2 years) in AI/ML research, software and/or embedded design, development and testing or related field
- Programming experience in one or more of the following languages: Python, C++, Rust, or MATLAB.
- Data‑preprocessing proficiency, including exploratory data analysis (EDA), data‑visualization tools, building ETL pipelines, and feature‑engineering techniques.
- Deep‑learning implementation experience with frameworks such as PyTorch, TensorFlow, Keras, or comparable libraries.
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