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Contractual Computer Vision Deep Learning Engineer Jobs in Virginia

Computer Vision AI Engineer

Mclean, VA · On-site

$99K - $225K/yr

Develop and implement deep learning computer vision models, with a focus on sensor fusion and ... Utilize GPU programming, including CUDA or RAPIDs, to optimize the performance of computer vision ...

Computer Vision AI Engineer

Mclean, VA · On-site

$99K - $225K/yr

Develop and implement deep learning computer vision models, with a focus on sensor fusion and ... Utilize GPU programming, including CUDA or RAPIDs, to optimize the performance of computer vision ...

Computer Vision AI Engineer

Mclean, VA · On-site

$99K - $225K/yr

Develop and implement deep learning computer vision models, with a focus on sensor fusion and ... Utilize GPU programming, including CUDA or RAPIDs, to optimize the performance of computer vision ...

Computer Vision AI Engineer

Mclean, VA · On-site

$99K - $225K/yr

Develop and implement deep learning computer vision models, with a focus on sensor fusion and ... Utilize GPU programming, including CUDA or RAPIDs, to optimize the performance of computer vision ...

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Contractual Computer Vision Deep Learning Engineer information

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Machine Learning Engineer - Computer Vision

CaseGuard

Arlington, VA • On-site

Full-time

Re-posted 25 days ago


Job description

Job Summary:
CaseGuard is a software company that helps various agencies manage their media redaction needs. They are seeking a highly skilled Machine Learning Engineer specializing in Computer Vision to design, implement, and optimize vision-based AI solutions focused on image and video processing.
Responsibilities:
• Design, develop, and deploy computer vision models for tasks such as object detection, object tracking, video segmentation, and facial recognition.
• Optimize and fine-tune deep learning algorithms for real-time performance.
• Work closely with the software engineers and product teams to identify opportunities for leveraging data.
• Collect, clean, and preprocess large datasets to prepare for model training and evaluation.
• Evaluate and optimize machine learning models for accuracy, performance, and scalability.
• Deploy models into production environments and monitor their performance to ensure reliability.
• Stay up-to-date with the latest advancements in computer vision and artificial intelligence.
• Collaborate with cross-functional teams to integrate machine learning solutions into business processes.
• Document processes, models, and implementations to ensure reproducibility and scalability.
Qualifications:
Required:
• Bachelor's or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
• Experience in deep learning models, their training, and hyperparameter tuning using libraries such as TensorFlow, PyTorch, and Transformers or other Huggingface tools.
• Experience with data manipulation tools such as Pandas, NumPy, and SQL.
• Strong programming skills in Python and C++.
• Experience in MLOps principles and model deployment and instrumentation on cloud platforms such as AWS, Azure, or Google Cloud for model deployment and knowledge with efficient serving tools such as ONNX, triton, and vllm.
• Proficiency in working with image and video data, including preprocessing and augmentation techniques.
• Strong understanding of machine learning algorithms, including supervised and unsupervised learning and deep learning.
• Strong communication skills and the ability to work collaboratively in a team environment.
Preferred:
• Familiarity with containerization and orchestration tools like Docker and Kubernetes.
• Experience with version control systems such as Git.
• Understanding software engineering best practices, including code review, testing, and documentation.
• Experience with Large Language Models (LLMs) is a great plus.
• Experience with data annotation tools and processes.
Company:
CaseGuard is a management solutions company. Founded in , the company is headquartered in Sterling, USA, with a team of 51-200 employees. The company is currently Growth Stage.