Staff Computer Vision AI/ML Engineer

CACI International — Block 2D, Altron Campus, 20 Woodlands Dr, Woodmead, Johannesburg, 2191, South Africa

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Job Title: Staff Computer Vision AI/ML EngineerJob Category: ScienceTime Type: Full timeMinimum Clearance Required to Start: TS/SCIEmployee Type: RegularPercentage of Travel Required: NoneType of Travel: NoneAnticipated Posting End: 12/31/2026The Opportunity:This position, in either Aurora, CO or King of Prussia, PA, is for a Staff Computer Vision AI/ML Engineer. As a CV AI/ML Engineer, you will apply cutting-edge AI/ML-based Computer Vision algorithms to problems in remote sensing, including Automatic Target Recognition ATR and Multimodal Data Fusion for Electro-Optical EO and Synthetic Aperture RADAR SAR. You will be responsible for maturing, optimizing, and deploying these algorithms to a cloud-hosted environment. You will also serve as a technical leader and will have the opportunity to guide a team of researchers and developers to see these algorithms from prototype to operations.Responsibilities:Our ideal candidate is an experienced professional who has researched and developed AI/ML-based computer vision algorithms and deployed these algorithms to operational environments. This candidate will have the opportunity to apply their knowledge in AI/ML to solve a broad set of problems across multiple domains. This candidate will be joining a team of talented researchers and software developers with the opportunity to lead and mentor junior engineers. Additionally, they will work our technical and business strategy leadership team to help shape our growing AI/ML portfolio.As a CV AI/ML Engineer, your responsibilities include: Leading a small team consisting of developers and researchers to implement AI/ML algorithms to solve computer vision problems in remote sensingAnalyzing and pre-processing large remote sensing datasetsResearching supervised and unsupervised ATR solutions for remote sensingResearching the performance benefits of multimodal data fusion for ATR, under diverse data collection scenariosTraining, optimizing, and deploying deep learning CV model




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