AI/ML Engineer Poly
Listed on 2026-02-13
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer, Data Scientist
Basic Qualifications
TS/SCI w/poly
2 years experience in applied machine learning in programs and contracts of similar scope, type, and complexity is required.
A B.S. degree in advanced math (e.g., calculus, linear algebra or Bayesian statistics), computer science or related STEM discipline from an accredited college or university is required.
3 years of additional machine learning experience (total of
5) on projects with similar machine learning processes may be substituted for a bachelor’s degree.
The Artificial Intelligence/Machine Learning (AI/ML) Engineer designs, creates, tests, and productizes AI/ML algorithms to solve business challenges. The AI/ML models they create should be capable of learning and making predictions as defined by the business logic developed to meet customer requirements. The AI/ML Engineer should be proficient in all aspects of model architecture, data pipeline interaction, and metrics application, interpretation, and presentation.
The AI/ML Engineer needs familiarity with foundational concepts of application development, infrastructure management, data engineering, and data governance. Through an understanding of training, retraining, deploying, scheduling, monitoring, and improving models through iterative user and system feedback, the AI/ML Engineer designs and creates scalable solutions for optimal performance. The AI/ML Engineer may be responsible for leading geographically diverse teams and will often serve as a primary POC for AI-related matters, so must have exceptional analytical, problem‑solving and communication skills.
We Are
At Lockheed Martin, we’re a pioneering aerospace and defense company that’s been at the forefront of innovation for decades. With a long‑standing history of pushing boundaries, we’re now shaping the future of cyber and intelligence. Our team is committed to innovating at the Edge, where we harness the latest advancements in Artificial Intelligence and Machine Learning, and cyber technologies to stay ahead of emerging threats and opportunities.
WhoYou Are
At Lockheed Martin, you will work with our team of skilled AI/ML Engineers design, create, test, and productize AI/ML algorithms that learn, predict, and make informed Expert knowledge of multiple programming languages (i.e. Python, Java, C++ decisions, meeting the evolving needs of our customers. With strong familiarity with Hadoop, we develop and deploy scalable AI/ML models that integrate with data pipelines, infrastructure, and applications.
WhyJoin Us
Providing ongoing training, mentorship, and development opportunities to help our cyber and intelligence professionals stay at the forefront of their field and achieve their career goals.
Competitive and comprehensive benefits package.
Rewards and recognition for your hard work.
Medical and dental coverage.
401k retirement savings plan.
Paid time off for work/life balance.
And more.
Desired SkillsAI/ML Engineer, responsible for building, training, fine‑tuning, and evaluating advanced language models. The ideal candidate will have hands‑on experience with state‑of‑the‑art machine learning techniques, specifically for natural language processing (NLP), and will also have a strong understanding of full‑stack development. This person will work across the model development lifecycle and collaborate with cross‑functional teams to deliver high‑impact solutions.
Key Responsibilities- Knowledge and experience of Language models is required
- Specific experience with Marian and multi‑lingual model development
- Knowledge of Computation Linguistics is a plus
- Experience with Open‑Source model libraries, Deep Learning Containers (DLC), GPU technologies and optimization / tuning
- Strong Java, C, C++ programming experience
- Willingness to support occasional on‑call duties is a plus
- Model Development & Training:
Build, train, and fine‑tune machine learning models, particularly language models - Apply best practices in model training, tuning, and optimization
- Design and implement solutions for model performance improvement
- Evaluation & Testing:
Conduct rigorous model evaluation, including performance analysis and benchmarking - Perform error analysis,…
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