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Computer Vision Scientist Jobs in Washington (NOW HIRING)

Computer Vision AI Engineer

Mclean, VA · On-site

$99K - $225K/yr

R0243890 Computer Vision AI Engineer The Opportunity: Booz Allen Hamilton is seeking an innovative ... In this role, you will leverage your expertise in artifi cia l intelligence, data science, and ...

Computer Vision AI Engineer

Mclean, VA · On-site

$99K - $225K/yr

R0243369 Computer Vision AI Engineer The Opportunity: Booz Allen Hamilton is seeking an innovative ... In this role, you will leverage your expertise in artifi cia l intelligence, data science, and ...

Computer Vision Researcher

Arlington, VA · On-site

$155K - $215K/yr

Team Description: Kitware's computer vision team is a leader in the creation of cutting-edge ... PhD in Computer Science or related field * Strong publication record in top-tier research ...

Team Description: Kitware's computer vision team is a leader in the creation of cutting-edge ... PhD in Computer Science or related field * Strong publication record in top-tier research ...

Computer Vision Researcher

Arlington, VA · On-site

$155K - $215K/yr

Team Description: Kitware's computer vision team is a leader in the creation of cutting-edge ... PhD in Computer Science or related field * Strong publication record in top-tier research ...

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Showing results 1-20

Computer Vision Scientist information

See Washington salary details

$57.2K

$126.1K

$155.7K

How much do computer vision scientist jobs pay per year?

As of Jul 14, 2026, the average yearly pay for computer vision scientist in Washington is $126,107.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,000.00 and $155,200.00 per year, depending on experience, location, and employer.

What is the difference between Computer Vision Scientist vs Machine Learning Engineer?

AspectComputer Vision ScientistMachine Learning Engineer
Required CredentialsMaster's or PhD in Computer Science, AI, or related fieldsBachelor's or Master's in Computer Science, Software Engineering, or related fields
Work EnvironmentResearch labs, R&D departments, academiaProduct teams, software development environments
Industry UsageDeveloping algorithms for image/video analysis, object detectionBuilding scalable ML models for various applications including vision

While both roles involve machine learning, Computer Vision Scientists focus on developing algorithms specifically for visual data, whereas Machine Learning Engineers implement and deploy these models in real-world applications. The roles often overlap but differ mainly in their primary focus and work environment.

What are the key skills and qualifications needed to thrive as a Computer Vision Scientist, and why are they important?

A Computer Vision Scientist needs a strong background in mathematics, machine learning, and image processing, often supported by a graduate degree in computer science or a related field. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), programming languages like Python or C++, and experience with libraries like OpenCV are typically required. Creative problem-solving, critical thinking, and effective communication help distinguish top performers in this role. These skills are essential for developing innovative computer vision solutions that can be effectively integrated into real-world applications.

What are some common challenges faced by Computer Vision Scientists when deploying models to production environments?

Computer Vision Scientists often encounter challenges such as ensuring model robustness under varying real-world conditions, optimizing inference speed for deployment on resource-constrained devices, and managing large-scale data for continuous model improvement. Collaboration with engineering teams is crucial to integrate models efficiently into existing software pipelines and to address issues like latency and scalability. Additionally, maintaining high accuracy while minimizing false positives and negatives in live environments requires ongoing monitoring and iterative improvement.

What are Computer Vision Scientists?

Computer Vision Scientists are professionals who develop algorithms and models that allow computers to interpret and understand visual information from the world, such as images and videos. They use techniques from machine learning, artificial intelligence, and image processing to solve problems like object detection, facial recognition, and scene understanding. Their work is essential in fields such as autonomous vehicles, healthcare imaging, robotics, and augmented reality. Computer Vision Scientists often collaborate with engineers and domain experts to create practical applications and improve existing technologies.
Cleared Computer Vision Scientist

Cleared Computer Vision Scientist

Accenture Federal Services

Washington, DC • On-site

Full-time

Posted 8 days ago


Accenture Federal Services rating

8.4

Company rating: 8.4 out of 10

Based on 19 frontline employees who took The Breakroom Quiz

50th of 449 rated business services


Job description

Job Summary:
Accenture Federal Services is dedicated to helping the US federal government enhance national security and public safety through technology. The Cleared Computer Vision Scientist will develop and optimize computer vision models and algorithms to provide mission value, collaborating with a team to ensure high-quality datasets and model performance.
Responsibilities:
• Develop, train, finetune and evaluate computer vision models in a wide range of topics, including geospatial, biometrics, 3D vision, semantic extraction, etc.
• Deploy, maintain, and optimize ML models and data processes in a production environment
• Develop custom Computer Vision (CV) algorithms that translate into mission value
• Create tools to provide feedback from production ML models and data processes
• Assist in the development and optimization of computer vision models using deep learning frameworks (e.g., PyTorch, TensorFlow).
• Collaborate with other scientists and engineers to build and deploy models for tasks such as object detection, image segmentation, classification, and tracking
• Stay up to date with the latest research and advancements in the field of computer vision and deep learning
• Participate in data collection, preprocessing, and augmentation processes to ensure high-quality datasets
• Conduct experiments, analyze results, and contribute to the improvement of model accuracy and efficiency
• Assist in the integration of computer vision algorithms into production systems and applications
• Document code, methodologies, and experimental results
Qualifications:
Required:
• Hands-on experience with computer vision libraries (e.g., OpenCV) and deep learning frameworks (e.g., PyTorch, TensorFlow)
• Proficiency with programming languages such as Python, C/C++ or Rust
• Strong understanding of CNNs, transformers and other advanced architectures and their applications in computer vision tasks
• Strong analytical and problem-solving skills
• Ability to work collaboratively in a team environment and take direction from senior team members
• Hands-on experience with developing computer vision models at scale from inception to business impact
• Design and develop custom/novel architectures, define use cases, and develop methodology & benchmarks to evaluate different approaches
• U.S. Citizenship (No Dual citizenship)
• Active Top Secret or TS/SCI or TS/SCI with polygraph Clearance
Preferred:
• Advanced Degree in computer science, technology, engineering, mathematics (STEM) related field, with Ph.D. preferred, but not required
• Hands-on experience with MLOps and CI/CD toolset including MLFlow, WandB, Airflow, Kubeflow, Gitlab CI or DVC
• Hands-on experience developing and deploying machine learning pipelines in AWS, Azure or GCP
• Hands on experience deploying, maintaining, testing, and optimizing ML models and data platforms in a production environment
• Hands-on experience with other image modalities (SAR, IR, HSI, Lidar, Sonar)
Company:
Accenture Federal Services is a leading US federal services company and subsidiary of Accenture. Founded in 1989, the company is headquartered in Arlington, USA, with a team of 10001+ employees. The company is currently Late Stage.

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