St. Louis, MO
84 days ago
Machine Learning Engineer (Active TS/SCI Clearance REQUIRED)

Why WWT?


Founded in 1990, World Wide Technology (WWT), a global technology solutions provider leading the AI and Digital Revolution, with $20 billion in annual revenue, combines the power of strategy, execution and partnership to accelerate digital transformational outcomes for large public and private organizations around the world. Through its Advanced Technology Center, a collaborative ecosystem of the world's most advanced hardware and software solutions, WWT helps customers and partners conceptualize, test and validate innovative technology solutions for the best business outcomes and then deploys them at scale through its global warehousing, distribution and integration capabilities.

With nearly 10,000 employees and more than 55 locations around the world, WWT's culture, built on a set of core values and established leadership philosophies, has been recognized 13 years in a row by Fortune and Great Place to Work® for its unique blend of determination, innovation and leadership focus on diversity and inclusion. With this culture at its foundation, WWT bridges the gap between business and technology to make a new world happen for its customers, partners and communities.

 

Want to work with highly motivated individuals on high-performance teams? Join WWT today!

 

As a Machine Learning Engineer you will help ensure today is safe and tomorrow is smarter. Our work depends on TS/SCI cleared Machine Learning Engineer joining our team to support our intelligence customer in St. Louis, MO.

 

HOW A MACHINE LEARNING ENGINEER WILL MAKE AN IMPACT

Own your opportunity to serve as a critical component of our nation's safety and security. Make an impact by using your expertise to protect our country from threats.

Rapidly prototype containerized multimodal deep learning solutions and associated data pipelines to enable GeoAI capabilities for improving analytic workflows and addressing key intelligence questions. You will be at the cutting edge of implementing State-of-the-Art (SOTA) Computer Vision (CV) and Vision Language Models (VLM) for conducting image retrieval, segmentation tasks, AI-assisted labeling, object detection, and visual question answering using geospatial datasets such as satellite and aerial imagery, full-motion video (FMV), ground photos, and OpenStreetMap.

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