Generative AI Engineer — Secret Clearance, Onsite Roles

Soc Llc; Washington (District of Columbia); On-site; USD 98,000 - 140,000; Full time

Job summary

SOC is hiring a Generative AI Engineer for a direct-hire engagement based in Washington, DC, onsite, with flexibility to sit in multiple US locations. A Secret Security Clearance is required.

This role sits on our AI & Data team building advanced AI platforms, services, and insights for clients in federal-health sectors. You will design, deploy, and optimize ML/AI solutions, build data pipelines, and collaborate with engineers, data scientists, and product stakeholders.

Qualifications

• BS in a quantitative field or related STEM degree.
• At least 2 years designing, developing, deploying ML/AI solutions.
• At least 2 years programming in Python, PySpark, PyTorch, and TensorFlow.
• At least 1 year of Federal Health technology consulting experience.
• Ability to travel ~20% and work in the US without sponsorship.

Responsibilities

• Design, build, test, and deploy ML/AI solutions for business and client use cases.
• Develop data pipelines, model training workflows, and production-grade components.
• Analyze structured and unstructured data to identify patterns and insights.
• Collaborate with engineers, data scientists, product stakeholders and business teams.
• Monitor model performance and improve accuracy, reliability, and scalability.

Skills

ML/AI design

Python & ML frameworks

Federal Health consulting

Model deployment knowledge

Education

Bachelor's degree in STEM

Master's degree preferred

Tools

Docker

Kubernetes

PyTorch

TensorFlow

PySpark

Job description

SOC is hiring a Generative AI Engineer for a direct-hire engagement based in Washington, DC, onsite, with flexibility to sit in multiple US locations. A Secret Security Clearance is required.

This role sits on our AI & Data team building advanced AI platforms, services, and insights for clients in federal-health sectors. You will design, deploy, and optimize ML/AI solutions, build data pipelines, and collaborate with engineers, data scientists, and product stakeholders.