AI Engineer - Entry to Expert Level (Maryland)

US National Security Agency/Central Security Service; Fort Meade (MD); On-site; USD 110,000 - 170,000; Full time

Job summary

NSA is seeking an AI Engineer to design, implement and maintain mission-critical AI systems across the full AI life cycle. You will apply data science, software, and systems engineering to build, deploy and monitor AI solutions for intelligence processing and reporting at Fort Meade.

Entry to Expert levels describe varied educational paths and relevant experience, including distributed AI/ML, platform engineering, cloud infrastructure, and DevOps.

Qualifications

• Experience implementing production-scale AI/ML solutions.
• Experience with distributed model training and AI/ML performance monitoring.
• Familiarity with platform and cloud infrastructure management, DevOps/MLOps.

Responsibilities

• Design, build and deploy AI/ML systems across the full life cycle.
• Lead distributed AI/ML projects, monitor performance and optimize models.

Skills

AI/ML solutions

DevOps

MLOps

Cloud engineering

Software engineering

Containerization

Education

Associate's degree

Bachelor's degree

Master's degree

Doctoral degree

Job description

As an AI Engineer at NSA, you will design & implement mission-critical AI systems that keep the agency at the cutting edge of intelligence collection, processing & reporting to keep the nation safe. You'll apply expertise in data science, plus software, data & systems engineering to build, deploy & maintain AI systems while addressing entire AI life cycle, including infrastructure management, efficient model training, production deployment, performance monitoring & continuous optimization.

ENTRY

Note that different degree fields have different requirements as described below. For degrees in Computer Science or Engineering, entry is with an Associate's degree plus 2 years of relevant experience, or a Bachelor's degree and no experience, or a Master's degree and no experience. For degrees in Information Systems, Information Technology, Mathematics, Applied Mathematics, Statistics, Applied Statistics, Operations Research, Artificial Intelligence, Data Science, or Physical or Biological Sciences, entry is with an Associate's degree plus 3 years of relevant experience, or a Bachelor's degree and 1 year of relevant experience. Relevant experience must be in one or more of the following: implementing production scale AI/ML (Artificial Intelligence / Machine Learning) solutions, distributed model training, distributed AI/ML systems, AI/ML performance monitoring, platform engineering, cloud engineering, developing deep learning models, neural networks, sustaining/maintaining AI/ML models, implementing AI/ML algorithms, AI/ML model development and deployment, DevOps, MLOps, cloud infrastructure management, software engineering, automated testing, or containerization.

FULL PERFORMANCE

Note that different degree fields have different requirements as described below. For degrees in Computer Science or Engineering, entry is with an Associate's degree plus 5 years of relevant experience, or a Bachelor's degree plus 3 years of relevant experience, or a Master's degree plus 1 year of relevant experience, or a Doctoral degree and no experience. For degrees in Information Systems, Information Technology, Mathematics, Applied Mathematics, Statistics, Applied Statistics, Operations Research, Artificial Intelligence, Data Science, or Physical or Biological Sciences, entry is with an Associate's degree plus 5 years of relevant experience, or a Bachelor's degree plus 3 years of relevant experience, or a Master's degree plus 1 year of relevant experience, or a Doctoral degree and 1 year of relevant experience. Relevant experience must be in one or more of the following: implementing production scale AI/ML solutions, distributed model training, distributed AI/ML systems, AI/ML performance monitoring, platform engineering, cloud engineering, developing deep learning models, sustaining/maintaining AI/ML models, implementing AI/ML algorithms, AI/ML model development and deployment, DevOps, MLOps, cloud infrastructure management, software engineering, automated testing, or containerization.

SENIOR

Entry is with an Associate's degree plus 8 years of relevant experience, or a Bachelor's degree plus 6 years of relevant experience, or a Master's degree plus 4 years of relevant experience, or a Doctoral degree plus 2 years of relevant experience. Degree must be in Computer Science, Engineering, Information Systems, Information Technology, Mathematics, Applied Mathematics, Statistics, Applied Statistics, Operations Research, Artificial Intelligence, Data Science, or Physical or Biological Sciences. Relevant experience must be in two or more of the following: implementing production scale AI/ML solutions, distributed model training, distributed AI/ML systems, AI/ML performance monitoring, platform engineering, cloud engineering, developing deep learning models, sustaining/maintaining AI/ML models, implementing AI/ML algorithms, AI/ML model development and deployment, DevOps, MLOps, cloud infrastructure management, software engineering, automated testing, or containerization.

EXPERT

Entry is with an Associate's degree plus 11 years of relevant experience, or a Bachelor's degree plus 9 years of relevant experience, or a Master's degree plus 7 years of relevant experience, or a Doctoral degree plus 5 years of relevant experience. Degree must be in Computer Science, Engineering, Information Systems, Information Technology, Mathematics, Applied Mathematics, Statistics, Applied Statistics, Operations Research, Artificial Intelligence, Data Science, or Physical or Biological Sciences. Relevant experience must be in three or more of the following: implementing production scale AI/ML solutions, distributed model training, distributed AI/ML systems, AI/ML performance monitoring, platform engineering, cloud engineering, developing deep learning models, sustaining/maintaining AI/ML models, implementing AI/ML algorithms, AI/ML model development and deployment, DevOps, MLOps, cloud infrastructure management, software engineering, automated testing, or containerization. Additionally, you must have experience in serving as an AI Project Team Leader/model owner.