Machine Learning Engineer 727

Role Overview

Responsibilities

• Design, train, validate, and deploy machine learning models.
• Build inference pipelines, feature engineering workflows, scalable AI APIs, and MLOps pipelines.
• Optimize model performance and resource utilization and monitor model drift.
• Deploy AI workloads into AWS environments and support computer vision, NLP, and geospatial AI initiatives.
• Gather and document customer requirements and assist with integration solutions.
• Document processes, procedures, integration patterns, and lessons learned.

Key Technologies

• Python, PyTorch, TensorFlow, Scikit-learn, Hugging Face, and MLflow.
• Docker or Podman, Kubernetes or EKS, ECS, Lambda, and SageMaker.
• GitLab CI/CD, Linux, PostgreSQL/PostGIS, Aurora, Oracle Spatial, Redis, and ElastiCache.
• GDAL, Rasterio, and OGR.

Required Qualifications

• Active TS/SCI clearance with eligibility for a CI Poly.
• Experience in software development, system integration, or technical support at the stated range of role levels.
• Customer or stakeholder experience in a technical or mission environment.
• Strong communication, coordination, requirements documentation, prioritization, Agile, and GitLab experience.

Desired Qualifications

• Production AI systems, computer vision, large language models, geospatial AI, AWS AI services, or satellite imagery experience.
• Secure data movement, enterprise service processes, scripting, geospatial development, data mapping, dashboards, or system integration experience.

Benefits

• Benefits include matching 401k, paid medical coverage, paid time off, paid training, tuition reimbursement, life and disability coverage, and competitive compensation.