Federal AI/ML Engineer — LLMs & RAG Systems

Worky; Washington (District of Columbia); On-site; USD 120,000 - 144,000; Full time

Benefits offered by this job

Competitive pay

Education stipends

Federal government work

Volunteer/community engagement

Growth opportunities

Supportive management

Job summary

Ignite Digital is hiring an AI/ML Engineer to independently contribute to developing advanced AI/ML systems and components for a large federal enterprise data ecosystem. You will work with autonomy, apply creative solutions, and influence major technical deliverables within a larger team project management environment.

Key responsibilities include building ML models, RAG architectures, scalable training infra, and production integration.

Qualifications

• Deep experience building LLM-based systems and RAG architectures.
• Proficiency with MLOps tools and cloud deployments on AWS/Azure/GCP.
• Advanced scripting in Python, JavaScript or Rust; independent worker.

Responsibilities

• Independently develop and optimize ML models, pipelines, and platform components.
• Build RAG architectures and high-performing inference systems.
• Create scalable infrastructure for training, experimentation and deployment.
• Lead integration of AI/ML models into production systems.
• Conduct advanced troubleshooting and performance tuning.
• Collaborate with stakeholders to accelerate mission-driven insights.

Skills

LLM-based systems

RAG architectures

MLOps tools

Python/JavaScript/Rust

AWS/Azure/GCP deployment

Education

Bachelor's degree in CS/engineering/math

Tools

MLFlow

Kubeflow

Airflow

AWS Bedrock

Databricks

Job description

Ignite Digital is hiring an AI/ML Engineer to independently contribute to developing advanced AI/ML systems and components for a large federal enterprise data ecosystem. You will work with autonomy, apply creative solutions, and influence major technical deliverables within a larger team project management environment.

Key responsibilities include building ML models, RAG architectures, scalable training infra, and production integration.