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Machine Learning Object Detection Jobs in Virginia

... Machine Learning, Computer Vision, and Object Detection. • Experience building and maintaining ETL pipelines, including Kubeflow pipelines. • Hands-on experience with imagery data, overhead ...

... Machine Learning, Computer Vision, and Object Detection. • Experience building and maintaining ETL pipelines, including Kubeflow pipelines. • Hands-on experience with imagery data, overhead ...

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Support development of computer vision and machine learning algorithms capable of detection, classifying, localizing, and tracking objects-of-interest from a group 1 UAV using the existing gimballed ...

... by machine learning algorithms • Generate representative synthetic data sets for systems ... object detection, and change detection in computer vision workflows • Familiarity with earth ...

... by machine learning algorithms • Generate representative synthetic data sets for systems ... object detection, and change detection in computer vision workflows • Familiarity with earth ...

... by machine learning algorithms • Generate representative synthetic data sets for systems ... object detection, and change detection in computer vision workflows • Familiarity with earth ...

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Machine Learning Object Detection information

What are the key skills and qualifications needed to thrive as a Machine Learning Object Detection Engineer, and why are they important?

To excel as a Machine Learning Object Detection Engineer, you need a solid background in computer science, mathematics, and deep learning principles, often backed by a relevant degree and experience in computer vision. Familiarity with frameworks like TensorFlow, PyTorch, and OpenCV, as well as experience with annotation tools and GPU computing, is typically required. Strong problem-solving abilities, attention to detail, and effective communication are vital soft skills for collaborating with cross-functional teams and addressing complex challenges. These competencies ensure accurate model development, efficient deployment, and continual improvement of object detection systems in real-world applications.

What are some common challenges faced when working on machine learning object detection projects?

One of the main challenges in machine learning object detection roles is dealing with the quality and quantity of annotated data, as accurate labeling is essential for model performance. Another common challenge is managing variations in object scale, lighting, and occlusion within real-world images, which can affect detection accuracy. Additionally, balancing model accuracy with computational efficiency—especially for real-time applications—often requires careful model selection and optimization. Collaboration with data engineers and domain experts is also typical to ensure data relevance and model applicability.

What is machine learning object detection?

Machine learning object detection is a field within artificial intelligence that focuses on identifying and locating objects within images or videos. It uses algorithms and deep learning models, such as convolutional neural networks (CNNs), to analyze visual data and predict the presence and position of various objects. Object detection is widely used in applications like autonomous vehicles, security surveillance, and image search. The process typically involves training models on labeled datasets so they can accurately detect and classify multiple objects in complex scenes.
What are popular job titles related to Machine Learning Object Detection jobs in Virginia? For Machine Learning Object Detection jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Machine Learning Object Detection jobs in Virginia look for? The top searched job categories for Machine Learning Object Detection jobs in Virginia are:
What cities in Virginia are hiring for Machine Learning Object Detection jobs? Cities in Virginia with the most Machine Learning Object Detection job openings:
Data Scientist with Security Clearance

Data Scientist with Security Clearance

NT Concepts

Herndon, VA • On-site

Other

Posted yesterday


Job description

Working at NT Concepts means that you are part of an innovative, agile company dedicated to solving the most critical challenges in National Security. We're looking for the best and the brightest to join us in supporting this mission. If meaningful work, initiative, creativity, and continuous self-improvement are important to your career, join our growing team and discover What's Next for you. Mission Focus: As a Data Scientist, you will contribute to a program advancing state-of-the-art modeling and prediction capabilities focused on object detection robustness. Working within a cross-functional team and reporting to a technical lead, you will operate across the machine learning development lifecycle, from data curation and synthetic data generation to model training, evaluation, and delivery.
Our delivery teams follow SAFe Agile practices, embrace the Ops ethos (DataOps/DevSecOps/MLOps) to "automate-first," and leverage modern tech stacks. This position requires a mid-to-senior level of experience, a passion for mission support, and a strong desire to solve our customers' hardest technical and data challenges. Clearance: Active TS Clearance with ability to obtain TS/SCI. US Citizenship is required. Location/Flexibility: Herndon, VA with remote flexibility. Must be local to the DC Metro area. Responsibilities Curate, transform, and optimize imagery data, including optical, Synthetic Aperture Radar (SAR), and synthetic data, for use by machine learning algorithms Design and maintain data conversion and ETL pipelines to prepare customer data for model training Generate and analyze synthetic data to augment computer vision models where real-world data is scarce Train, evaluate, and optimize deep neural network models on overhead imagery, including hyperparameter tuning and performance analysis Perform exploratory data analysis, feature engineering, and preprocessing to improve model performance Develop and visualize explainable AI metrics and model performance indicators Incorporate research and development outputs into the operational code base Communicate analytic findings to both technical and non-technical stakeholders Contribute to solutioning sessions and technical sections of project proposals Required Qualifications 5+ years of experience in data science, machine learning, or a related field Hands-on experience with data curation techniques for overhead imagery (optical or SAR) and computer vision model development Experience building and maintaining ETL or data processing pipelines Proficiency in Python and familiarity with machine learning and deep learning libraries such as PyTorch Experience with Git-based version control systems Proficiency working in the Linux operating system Strong analytical and problem-solving skills Ability to work in a fast-paced, collaborative, Agile environment Eligibility to work in classified environments and hold required security clearances Preferred Qualifications Experience with synthetic data generation and analysis for computer vision applications Experience with cloud-based or distributed computing platforms Experience deploying models into production and supporting ongoing operations and maintenance Experience communicating technical results to non-technical audiences or contributing to customer-facing deliverables Awareness of emerging data science, AI/ML, and big-data technologies relevant to national security missions Experience contributing to technical proposals #JT