AI/ML Research Engineer

Peraton

. Lead the design and implementation of the machine learning core for research and development into generative models .

Posted 9/15/2026full-timeRed Bank • New Jersey • United StatesMid-LevelSenior💰 $146,000 - $234,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in machine learning model design, implementation, and optimization, with a strong focus on causal inference and probabilistic modeling. Proficient in building and maintaining ML infrastructure, including training pipelines and containerized frameworks, while effectively communicating complex model behaviors to diverse stakeholders.

Highest-signal resume keywords

Machine Learning Core DesignCausal Inference and Structural Causal ModelsPython Software EngineeringProduction-Quality PyTorch ImplementationMulti-Objective Optimization

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Machine LearningCausal InferenceProbabilistic Graphical ModelsBayesian NetworksProbabilistic ProgrammingContainerizationModel VersioningExperiment ManagementDataset VersioningOptimization Algorithms

Soft Skills

Clear CommunicationCollaboration

Tools & Technologies

PyTorchGPU Performance ProfilingML Infrastructure

Certifications & Qualifications

US CitizenshipSecret Security Clearance

Industry Keywords

Generative ModelsSynthetic Data GenerationResearch and DevelopmentTechnical Documentation

Tech Stack

Tools & technologies

PythonPyTorch

About the role

Key responsibilities & impact

Lead the design and implementation of the machine learning core for research and development into generative models
Formulate models and build training and inference pipelines
Integrate models with synthetic and laboratory datasets
Deliver trained, containerized frameworks
Design, implement, and train causal graph models and planning algorithms
Architect approaches to multi-objective optimization
Build and maintain ML infrastructure, including training and inference pipelines, experiment tracking, model versioning, dataset loaders, and objectives and interfaces
Package trained models as containerized inference components conforming to specified APIs
Work with the Lead System Integrator to deliver regular code drops and major code revisions
Contribute to synthetic data generation and simulation campaigns
Present research results at program design reviews, site visits, and PI workshops
Author technical sections of monthly status reports and design documentation
Coordinate with academic subcontractor researchers on shared model components
Collaborate with RF, DSP, and formal methods engineers

Requirements

What you’ll need

5+ years of experience
MS or PhD in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, or a related technical field
2+ years of applied machine learning research experience
Demonstrated work in causal inference and structural causal models, Bayesian networks and probabilistic graphical models, probabilistic programming, or learned optimization and planning
Strong Python software engineering skills
Production-quality use of PyTorch, including custom model implementation, training loop design, and GPU performance profiling
Experience translating research prototypes into maintainable, tested, containerized code
Working knowledge of multi-objective and constrained optimization and experience applying it to structured design spaces
Experience with experiment management, reproducible ML pipelines, and dataset versioning on a multi-person research team
Ability to implement methods from current research literature
Ability to communicate model behavior and limitations clearly to non-ML engineers and government stakeholders
US Citizenship
Willingness and ability to obtain Secret security clearance

Benefits

Comp & perks

Employees may be eligible for overtime
Employees may be eligible for shift differential
Employees may be eligible for a discretionary bonus
Equal opportunity employment, including disability and protected veterans or other characteristics protected by law