SCI w Poly

Peraton•Laurel, MD

11d

About The Position

Peraton is hiring an AI/ML Engineer to design, develop, test, and operationalize algorithms that address complex business challenges and mission requirements. The role builds data-driven models that generate predictions aligned with customer-defined business logic and operational needs, and applies expertise in model architecture, data pipeline integration, and performance metrics. The engineer trains, retrains, deploys, schedules, monitors, and continually improves models in response to user and system feedback, delivering scalable, high-performance solutions. The position requires a strong understanding of application development, infrastructure management, data engineering, and data governance. The engineer may lead geographically distributed teams and often serves as the primary technical point of contact for related matters. The work includes selecting datasets and representation methods, applying statistical analysis, researching and implementing AI/ML algorithms, transforming prototypes into production solutions, overseeing system integration, and verifying data integrity and model output quality. The engineer also runs and oversees iterative testing, evaluation, verification, and validation processes.

Requirements

At least 5 years of applied machine learning experience on programs or contracts of similar scope, type, and complexity.
Master’s or Ph.D. in Advanced Mathematics, Artificial Intelligence, Data Science, Computer Science, or Deep Learning from an accredited college or university; alternatively, a relevant bachelor’s degree plus 5 additional years of machine learning experience may substitute for a master’s degree.
Active TS/SCI with Poly clearance.
Experience with machine learning libraries, packages, and frameworks, including PyTorch or TensorFlow.
Proficiency in model architecture, data pipeline integration, and applying, interpreting, and presenting performance metrics.
Understanding of application development, infrastructure management, data engineering, data governance, software architecture, data modeling, and data structures.
Strong analytical thinking, problem-solving ability, and communication skills.

Nice To Haves

Expert knowledge of multiple programming languages, such as Python, Java, C, and R.
Eligibility for enhanced professional development opportunities, including training, certification programs, and skill-building experiences tailored to individual strengths, career goals, and role-specific requirements.

Responsibilities

Design, develop, test, and operationalize algorithms for complex business challenges and mission requirements.
Build models that learn from data and produce predictions aligned with customer-defined business logic and operational needs.
Apply model architecture, data pipeline integration, and performance metrics expertise.
Train, retrain, deploy, schedule, monitor, and continuously improve models based on user and system feedback.
Select appropriate datasets and data and knowledge representation methods for machine learning applications.
Perform statistical analysis and data interpretation; run and evaluate machine learning algorithms; and use results to improve and optimize models.
Research and implement a broad range of AI/ML algorithms and tools.
Transform data science prototypes into scalable production solutions and provide system integration oversight.
Verify data integrity and model output quality, and identify data distribution differences that may affect model performance.
Run standard testing and evaluation protocols and oversee iterative testing and evaluation of AI/ML algorithms.
Ensure solutions meet verification and validation requirements.
May lead geographically distributed teams and serve as the primary point of contact for related technical matters.

Benefits

Heavily subsidized employee benefits coverage for employees and their dependents.
25 days of PTO accrued annually, up to a generous PTO cap.
Eligibility to participate in a bonus plan.
Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.
Selected candidates may be eligible for enhanced professional development opportunities, including training, certification programs, and skill-building experiences.

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