Onsite ML Systems Engineer — TS/SCI Clearance

GRVTY; Springfield (VA); On-site; USD 150,000 - 165,000; Full time

Benefits offered by this job

Health benefits

Competitive compensation

Paid time off

Job summary

GRVTY in Springfield, VA is seeking a hands-on ML engineer to design, build, and maintain ML systems that automate decision-making. The role blends software engineering with ML expertise and is onsite in the Springfield area.

You will develop models and end-to-end pipelines, deploy them as APIs, monitor performance, and retrain with new data while integrating with applications and cloud platforms. Strong credentials in Kubernetes, Python, and ML tooling are required for this role.

Qualifications

• US Citizenship with TS/SCI and ability to obtain a CI Polygraph.
• Bachelor’s degree in a relevant field with 8 years of experience.
• Expert knowledge of Kubernetes and Python; experience with Git, Linux, REST APIs.
• Backend development experience: API design, database integration, Docker.
• Experience with MLops tooling and workflow orchestration (MLflow, Kubeflow, Argo Workflows, or Airflow).
• Expert ML algorithms: supervised/unsupervised learning, NLP, PyTorch or TensorFlow.

Responsibilities

• Model Development: Create and train ML models for classification, regression, forecasting, or deep learning.
• Pipeline Design: Build end-to-end ML pipelines for data preprocessing, feature engineering, model training, and evaluation.
• Deployment: Deploy models as APIs or backend services using frameworks like FastAPI, Flask, or Django.
• Monitoring & Maintenance: Track model performance, detect drift, and retrain with new data.
• Integration: Connect ML systems to applications, databases, and cloud platforms.

Skills

Kubernetes

Python

REST APIs

ML model development

Data engineering

Education

Bachelor's Degree in relevant field

Master's Degree in relevant field

Tools

Docker

Git

Linux

FastAPI

Job description

GRVTY in Springfield, VA is seeking a hands-on ML engineer to design, build, and maintain ML systems that automate decision-making. The role blends software engineering with ML expertise and is onsite in the Springfield area.

You will develop models and end-to-end pipelines, deploy them as APIs, monitor performance, and retrain with new data while integrating with applications and cloud platforms. Strong credentials in Kubernetes, Python, and ML tooling are required for this role.