HOW ML/OPs WILL MAKE AN IMPACT
Create and maintain custody of production machine learning models across a variety of tasks, including but not limited to audio extraction, object recognition, Natural Language Processing (NLP), and other generic classification tasks
Optimize existing machine learning services to better utilize current GPU capabilities and assist with road mapping future GPU requirements
Deploy machine learning models against streaming data, designed to provide near-real time analytics to augment decision making
Improve data architecture decisions with data engineers to better stage data for continuous training models in production
Provide support in the areas of data extraction, transformation and load (ETL), data mapping, analytics, operations, databases, and maintenance of data and associated systems
WHAT YOU’LL NEED TO SUCCEED
The position requires an active TS/SCI with Polygraph security clearance
The position requires fifteen (15+) years of related experience
Develop and manage infrastructure for model training, deployment, and serving across on-prem environments
Manage containerization and orchestration of ML services (e.g., Docker, Kubernetes)
Build and maintain CI/CD pipelines for machine learning models and data workflows
Collaborate with data scientists, data engineers, and software developers to operational ML solutions
Troubleshoot production issues and optimize system reliability, scalability, and cost
Document processes, standards, and best practices for ML operations
Automate model packaging, versioning, testing, and release processes
Implement monitoring for model performance, data quality, drift, latency, and system health
Maintain reproducible environments and experiment tracking for model development
Support data and model governance, including security, access controls, and auditability
Location: At Customer Site - near Tysons Corner
GDIT IS YOUR PLACE
401K with company match
Comprehensive health and wellness packages
