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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 five 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 from an accredited college or university is required.
  • A relevant bachelor’s degree plus five additional years of machine-learning experience may be substituted for a master’s degree.
  • An active TS/SCI with Poly clearance is required.
  • Experience 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.
  • Ability to transform data science prototypes into scalable production solutions is required.
  • Ability to provide system integration oversight is required.
  • Ability to select appropriate datasets for machine-learning applications is required.
  • Ability to perform statistical analysis and data interpretation is required.
  • Ability to run and evaluate machine-learning algorithms is required.
  • Ability to use analytical results to improve and optimize models is required.
  • Ability to train and retrain systems as required is required.
  • Ability to research and implement a broad range of artificial intelligence and machine-learning algorithms and tools is required.
  • Ability to verify data integrity and model output quality is required.
  • Ability to identify data distribution differences that may impact model performance is required.
  • Ability to run standard testing and evaluation protocols is required.
  • Ability to oversee testing and evaluation of artificial intelligence and machine-learning algorithms through iterative design processes is required.
  • 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, including interpreting and presenting the metrics.
  • Maintain an understanding of application development, infrastructure management, data engineering, and data governance concepts.
  • Train, retrain, deploy, schedule, monitor, and continuously improve models based on iterative user and system feedback to deliver scalable, high-performance solutions.
  • Lead geographically distributed teams as needed and serve as the primary point of contact for related technical matters.
  • Select appropriate data and knowledge representation methods; apply software architecture, data modeling, and data structure principles; transform prototypes into scalable production solutions; and provide system integration oversight.
  • Select datasets, conduct statistical analysis and data interpretation, run and evaluate algorithms, and use results to optimize models.
  • Research and implement AI/ML algorithms and tools, verify data integrity and model output quality, and identify data distribution differences that could affect model performance.
  • 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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