ML) Engineer 3

Peraton•Laurel, MD

2d•$176,000 - $282,000

About The Position

The Artificial Intelligence/Machine Learning (AI/ML) Engineer 3 serves as the technical lead for enterprise AI/ML initiatives, responsible for building, scaling, and guiding a team of engineers and practitioners. Partners with customer technical leadership to define, shape, and execute the AI/ML roadmap, bringing together deep technical expertise and strong business acumen. Responsible for developing strategy, managing stakeholder relationships, and enabling scalable, high-performing teams. Designs, develops, tests, and operationalizes algorithms to solve complex business challenges and mission-critical requirements. Builds models capable of learning from data and generating predictions aligned with customer-defined business logic and objectives. Demonstrates expertise across model architecture, data pipeline integration, and the application, interpretation, and communication of performance metrics. Maintains strong foundational knowledge of application development, infrastructure management, data engineering, and data governance to support scalable enterprise solutions. Responsible for training, retraining, deploying, scheduling, monitoring, and continuously improving models based on iterative user and system feedback to ensure optimal performance. Leads geographically distributed teams and frequently serves as the primary technical point of contact for related matters, requiring strong analytical thinking, problem-solving ability, and exceptional communication skills. Proficient in multiple programming languages such as Python, Java, C, and R. Key Role – Technical Leadership Responsibilities Serve as primary technical point of contact for all AI/ML-related matters with customers and stakeholders Lead the design, development, testing, and productization of AI/ML capabilities for mission-critical challenges Define and execute AI/ML strategy and roadmaps aligned with mission objectives and customer requirements Advise on emerging research areas and technical advancements to support both near-term and long-term goals Build, lead, and scale a diverse technical team, including hiring, mentoring, and professional development Contribute to workforce planning, labor category definition (LCAT), and staffing strategy as programs mature Represent capabilities in customer-facing briefings, engagements, and technical reviews Provide end-to-end system integration oversight across pipelines and enterprise systems Transform prototypes into scalable, production-ready enterprise solutions Design, evaluate, and operationalize models across commercial cloud-based architectures.

Requirements

Minimum of 10 years of experience deploying machine learning algorithms.
Master’s or Ph.D. in advanced mathematics, artificial intelligence, data science, computer science, or deep learning from an accredited college or university.
A Bachelor’s degree plus 7 additional years of relevant experience may substitute for a Master’s degree
Demonstrated expertise in software engineering and model testing and evaluation
An active TS/SCI with Poly is required.
Proficient in multiple programming languages such as Python, Java, C, and R.

Nice To Haves

Familiarity with Large Language Models (LLMs)
Experience with Retrieval-Augmented Generation (RAG) frameworks
Knowledge of AI agents and agentic workflows
Expert knowledge of multiple programming languages, e.g. Python, Java, C, R, is desired.

Responsibilities

Serve as primary technical point of contact for all AI/ML-related matters with customers and stakeholders
Lead the design, development, testing, and productization of AI/ML capabilities for mission-critical challenges
Define and execute AI/ML strategy and roadmaps aligned with mission objectives and customer requirements
Advise on emerging research areas and technical advancements to support both near-term and long-term goals
Build, lead, and scale a diverse technical team, including hiring, mentoring, and professional development
Contribute to workforce planning, labor category definition (LCAT), and staffing strategy as programs mature
Represent capabilities in customer-facing briefings, engagements, and technical reviews
Provide end-to-end system integration oversight across pipelines and enterprise systems
Transform prototypes into scalable, production-ready enterprise solutions
Design, evaluate, and operationalize models across commercial cloud-based architectures
Designs, develops, tests, and operationalizes algorithms to solve complex business challenges and mission-critical requirements.
Builds models capable of learning from data and generating predictions aligned with customer-defined business logic and objectives.
Demonstrates expertise across model architecture, data pipeline integration, and the application, interpretation, and communication of performance metrics.
Maintains strong foundational knowledge of application development, infrastructure management, data engineering, and data governance to support scalable enterprise solutions.
Responsible for training, retraining, deploying, scheduling, monitoring, and continuously improving models based on iterative user and system feedback to ensure optimal performance.
Leads geographically distributed teams and frequently serves as the primary technical point of contact for related matters, requiring strong analytical thinking, problem-solving ability, and exceptional communication skills.