AI/ML Engineer - Hybrid DC, FedRAMP & MLOps

Digital Links Inc; Washington (District of Columbia); Hybrid; USD 120,000 - 150,000; Full time

Benefits offered by this job

Job summary

Digital Links Inc in Washington, DC is seeking an experienced AI/ML engineer to design and deliver enterprise AI applications. The role focuses on building production-ready solutions that leverage LLMs, NLP, and document intelligence, with emphasis on security and compliant environments.

You will work in a hybrid setup (3 days onsite) and collaborate across data, product, and security teams to deploy robust pipelines, ML models, and automation using Python, APIs, and cloud services.

Qualifications

• 3+ years relevant experience, including 2+ years AI/ML delivery.
• Hands-on Python, APIs, data pipelines, Git, testing and cloud delivery.
• Experience with LLM, RAG, NLP, document intelligence or predictive ML.
• Build AI applications, automation, integrations and production solutions.
• Experience with MLOps/DevSecOps, CI/CD, monitoring and evaluation.
• Knowledge of security, PII, accessibility and regulated environments.
• Federal/FedRAMP experience preferred.

Responsibilities

• Build AI applications and automation, delivering production-ready solutions.
• Develop integrations and data pipelines for scalable AI systems.
• Implement MLOps practices and CI/CD pipelines.
• Monitor, evaluate and improve model performance and security.

Skills

AI/ML implementation

Python

APIs

Data pipelines

Git

Testing and cloud delivery

LLM and NLP

RAG

Document intelligence

Predictive ML

MLOps/DevSecOps

CI/CD

Monitoring and evaluation

Security and PII handling

FedRAMP experience

Job description

Digital Links Inc in Washington, DC is seeking an experienced AI/ML engineer to design and deliver enterprise AI applications. The role focuses on building production-ready solutions that leverage LLMs, NLP, and document intelligence, with emphasis on security and compliant environments.

You will work in a hybrid setup (3 days onsite) and collaborate across data, product, and security teams to deploy robust pipelines, ML models, and automation using Python, APIs, and cloud services.