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Peraton

Runs and secures technology for federal agencies

Artificial Intelligence/Machine Learning Engineer 2

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeLaurel, MD, USAIn-person

About the Job

Requirements

  • A minimum of 5 years of experience in applied machine learning on programs or contracts of similar scope, type, and complexity is required.
  • A Master's or Ph.D. degree in Advanced Mathematics, Artificial Intelligence, Data Science, Computer Science, or Deep Learning is required. A relevant Bachelor's degree plus 5 additional years of machine learning experience may be substituted for a Master's degree.
  • U.S. citizenship is required.
  • The ability to obtain and maintain an active TS/SCI with Poly before the start date is required.
  • Experience working with machine learning libraries, packages, and frameworks is required.
  • Experience with standard machine learning frameworks such as PyTorch or TensorFlow is required.
  • Knowledge of data and knowledge representation methods is required.
  • Knowledge of software architecture, data modeling, and data structure principles is required.
  • The ability to transform data science prototypes into scalable production solutions is required.
  • The ability to provide system integration oversight is required.
  • The ability to select appropriate datasets for machine learning applications is required.
  • The ability to perform statistical analysis and data interpretation is required.
  • The ability to run and evaluate machine learning algorithms is required.
  • The ability to use analytical results to improve and optimize models is required.
  • The ability to train and retrain systems is required.
  • The ability to research and implement a broad range of AI/ML algorithms and tools is required.
  • The ability to verify data integrity and model output quality is required.
  • The ability to identify data distribution differences that may impact model performance is required.
  • The ability to run standard testing and evaluation protocols is required.
  • The ability to oversee testing and evaluation of AI/ML algorithms through iterative design processes is required.
  • The ability to ensure solutions meet verification and validation requirements is required.

Responsibilities

  • Design, develop, test, and operationalize algorithms to solve complex business challenges and mission requirements.
  • Build models that learn from data and generate predictions aligned with customer-defined business logic and operational needs.
  • Apply model architecture, data pipeline integration, and performance metrics; interpret and present metric results.
  • Apply foundational concepts in application development, infrastructure management, data engineering, and data governance.
  • Train, retrain, deploy, schedule, monitor, and continuously improve models using iterative user and system feedback to deliver scalable, high-performance solutions.
  • May lead geographically distributed teams and frequently serve as the primary point of contact for related technical matters.
  • Select appropriate data and knowledge representation methods.
  • Provide system integration oversight.
  • Select appropriate datasets for machine learning applications; perform statistical analysis and data interpretation; run and evaluate machine learning algorithms; and use analytical results to optimize models.
  • Research and implement AI/ML algorithms and tools, and verify data integrity and model output quality.
  • Run standard testing and evaluation protocols, oversee iterative testing and evaluation of AI/ML algorithms, and ensure solutions meet verification and validation requirements.

Desired Qualifications

  • Expert knowledge of multiple programming languages, such as Python, Java, C, or R.

About the Company

Peraton

Runs and secures technology for federal agencies

Peraton builds and runs secure technology for American defense, intelligence, space, and civilian agencies, from military networks to satellite ground stations. In 2025, the Federal Aviation Administration chose it to manage the overhaul of the nation's air traffic control system, replacing copper wiring with fiber and upgrading radar and radios. Its engineers, many holding security clearances, run and defend agency networks and data centers, write mission software, and operate space and communications systems, and agencies pay for this work through multiyear contracts. Peraton was formed in 2017, when private-equity firm Veritas Capital bought Harris Corporation's government IT business, and is based in Reston, Virginia.

Company size
10,001+
Company stage
Grant
Total funding
$60M
Headquarters
Reston, VA
Founded
2017

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