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Contractual Computer Vision Deep Learning Engineer Jobs in Chantilly, VA

Booz Allen Hamilton

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 ...

Booz Allen Hamilton

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 ...

Booz Allen Hamilton

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 ...

Booz Allen Hamilton

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

See Chantilly, VA salary details

$19

$61

$83

How much do contractual computer vision deep learning engineer jobs pay per hour?

As of Aug 3, 2026, the average hourly pay for contractual computer vision deep learning engineer in Chantilly, VA is $61.01, according to ZipRecruiter salary data. Most workers in this role earn between $53.17 and $67.93 per hour, depending on experience, location, and employer.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and while AI automation tools can handle some tasks, MLEs are essential for creating and maintaining complex systems. AI may augment their work, but it is unlikely to fully replace the need for skilled professionals who understand data, algorithms, and deployment environments.

What engineers make $300,000 a year?

Senior computer vision deep learning engineers with extensive experience, advanced skills in neural networks, and proficiency in frameworks like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-demand industries such as autonomous vehicles, AI research, or tech giants. Compensation often includes base salary, bonuses, and stock options, and typically requires advanced degrees and a strong track record of project success.

What engineer makes $500,000 a year?

A Contractual Computer Vision Deep Learning Engineer can earn $500,000 or more annually, especially with extensive experience, specialized skills in deep learning frameworks like TensorFlow or PyTorch, and working on high-impact projects for leading tech companies or research institutions. Such roles often require advanced degrees, strong programming skills, and a track record of successful deployments in AI applications.

What engineers make $200,000 a year?

Senior computer vision deep learning engineers with extensive experience, advanced skills in neural networks, and proficiency in frameworks like TensorFlow or PyTorch can earn $200,000 or more annually. These roles often require a strong educational background, specialized certifications, and work in high-demand industries such as technology, autonomous vehicles, or healthcare AI.
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Machine Learning Engineer - Computer Vision

CaseGuard

Arlington, VA • On-site

Full-time

Re-posted 23 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.

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