Artificial Intelligence/Machine Learning Engineer

Analytica

Remote AI/ML Engineer developing secure models and MLOps pipelines for Analytica’s U.S. federal health, civilian, and national security missions.

Posted 8/5/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying machine learning and AI models, with a strong focus on MLOps, NLP, and generative AI solutions. Proficient in optimizing model performance and integrating AI capabilities into various applications and workflows.

Highest-signal resume keywords

Machine Learning EngineeringMLOps Pipeline DevelopmentPython ProgrammingNLP and Generative AIModel Deployment and Monitoring

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningAI Model DevelopmentPredictive AnalyticsModel EvaluationData ScienceModel OptimizationAutomation SolutionsCloud AI ServicesModel VersioningSecurity and Reliability

Soft Skills

Analytical SkillsDocumentation SkillsCommunication SkillsCollaboration Skills

Tools & Technologies

PyTorchTensorFlowScikit-learnMLOps ToolsAPIsReporting PlatformsOperational Workflows

Certifications & Qualifications

IRS MBI Clearance

Industry Keywords

IRSTreasuryFraud AnalyticsTax AdministrationFederal AI/ML Experience

Tech Stack

Tools & technologies

CloudPythonPyTorchScikit-LearnTensorflow

About the role

Key responsibilities & impact

Develop, train, evaluate, deploy, and monitor machine learning and AI models for mission and business use cases
Build and support MLOps pipelines for model versioning, deployment, monitoring, and governance
Collaborate with data engineers, application developers, analysts, and domain SMEs to operationalize AI capabilities
Implement NLP, LLM, RAG, generative AI, predictive analytics, and automation solutions where appropriate
Optimize model performance, scalability, explainability, security, and reliability
Support AI solution integration into APIs, applications, reporting platforms, and operational workflows
Document model development, testing, deployment, monitoring, and responsible AI considerations

Requirements

What you’ll need

3+ years of AI/ML engineering, data science, or applied machine learning experience
Experience with Python and ML frameworks such as PyTorch, TensorFlow, or scikit-learn
Experience with MLOps tools, cloud AI services, model deployment, and production monitoring
Knowledge of NLP, LLMs, RAG, generative AI, predictive modeling, and model evaluation methods
Experience deploying AI/ML capabilities within secure cloud or enterprise environments
Strong analytical, documentation, communication, and collaboration skills
IRS, Treasury, fraud analytics, tax administration, or federal AI/ML experience preferred
Must have active or ability to obtain IRS MBI clearance

Benefits

Comp & perks

Competitive compensation
Opportunities for bonuses
Employer paid health care
Training and development funds
401k match
Reasonable accommodations for applicants and employees with disabilities