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Computer Vision Scientist Jobs in Maryland (NOW HIRING)

asrcfh

Junior Data Scientist

Greenbelt, MD · On-site

Position Overview: Seeking a Data Scientist or Machine Learning with proven experience in ... learning, computer vision, and natural language processing, with demonstrated success in both ...

New

ASRC Federal Holding

Junior Data Scientist

Greenbelt, MD · On-site

$64K - $96K/yr

Position Overview: Seeking a Data Scientist or Machine Learning with proven experience in ... computer vision, and natural language processing, with demonstrated success in both academic and ...

New

AeroVironment

Computer Scientist

Annapolis Junction, MD · On-site

$125K - $219K/yr

Worker Type Regular The Computer Scientist plays a pivotal role in ensuring the reliability ... AV offers an excellent benefits package including medical, dental vision, 401K with company ...

AeroVironment, Inc.

Computer Scientist

Annapolis, MD · On-site

$125K - $219K/yr

Worker Type Regular The Computer Scientist plays a pivotal role in ensuring the reliability ... AV offers an excellent benefits package including medical, dental vision, 401K with company ...

Prescient Edge

Senior Computer Scientist

Bethesda, MD · On-site

$130K - $190K/yr

Job Title Senior Computer Scientist Location Bethesda, MD 20800 US (Primary) Category Research ... Comprehensive healthcare benefits, including medical, vision, dental, and orthodontia coverage. * A ...

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All JobsComputer Vision Scientist JobsComputer Vision Scientist Jobs in Maryland

Computer Vision Scientist information

See Maryland salary details

$49K

$108.1K

$133.4K

How much do computer vision scientist jobs pay per year?

As of Aug 23, 2026, the average yearly pay for computer vision scientist in Maryland is $108,063.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,700.00 and $133,000.00 per year, depending on experience, location, and employer.

What is a computer vision scientist?

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.

What are the key skills and qualifications needed to thrive as a computer vision scientist?

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 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 popular job titles related to Computer Vision Scientist jobs in Maryland?

For Computer Vision Scientist jobs in Maryland, the most frequently searched job titles are:

What job categories do people searching Computer Vision Scientist jobs in Maryland look for?

The top searched job categories for Computer Vision Scientist jobs in Maryland are:

Computer Vision Scientist jobs near you
Infographic showing various Computer Vision Scientist job openings in Maryland as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 17% Part Time, and 5% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $108,063 per year, or $52 per hour.

Junior Data Scientist

asrcfh

Greenbelt, MD • On-site

Full-time

Posted 2 days ago

New

Job description

ASRC Federal AFSS is a premier provider of systems engineering, software engineering, system integration and project management services for real-time, mission-critical defense systems. We are seeking a Data Scientist / Machine Learning to provide junior-level support a NASA contract in Greenbelt, MD.

Responsibilities:

Position Overview:
Seeking a Data Scientist or Machine Learning with proven experience in developing advanced machine learning models, statistical analysis, and multimodal data systems for large, complex datasets. The ideal candidate will have a strong background in Python-based modeling, deep learning, computer vision, and natural language processing, with demonstrated success in both academic and research environments, including NASA projects.

Key Responsibilities:

  • Develop, implement, and optimize machine learning and deep learning models for scientific and real-world applications, including vision-language systems and multimodal architectures.
  • Construct and manage large-scale datasets (e.g., image-text pairs) for model training and evaluation.
  • Design and execute multi-stage inference pipelines, evaluation frameworks, and fine-tuning strategies to improve model reliability and accuracy.
  • Apply statistical modeling and time series forecasting techniques (e.g., SARIMA, LSTM) to predict trends in domains such as sustainable aviation fuels and green hydrogen.
  • Analyze complex datasets using regression, NLP, and quantitative methods to extract actionable insights for policy and research.
  • Collaborate with cross-functional teams, including NASA scientists and academic researchers, to disseminate findings through publications and presentations.
  • Author technical documentation and present diagnostics and results at conferences and symposiums.
  • Teach and mentor students in data analytics and computer science, developing supplementary materials and project-based modules.
  • Additional duties as assigned.

 

Required Qualifications:

  • Bachelor’s degree in Data Science, Statistics, or related discipline.
  • Strong programming skills: Python, R, SQL, MATLAB, SAS, HTML/CSS; experience with PyTorch, TensorFlow, Linux, Git.
  • Expertise in machine learning, deep learning, time series forecasting, statistical modeling, computer vision, NLP, and multimodal learning.
  • Experience with data preprocessing, feature engineering, data visualization, and quantitative analysis.
  • Demonstrated ability to build scalable data pipelines and process large, unstructured datasets.
  • Excellent communication skills, with experience presenting technical findings to diverse audiences.
  • Individual must meet government NAC and citizenship/permanent residency requirements for access to NASA GSFC. Extensive background investigation will be performed as a requirement of the job. Some travel may be required.

Preferred Experience:

  • Research experience in academic or government settings (e.g., NASA).
  • Experience developing vision-language models and multimodal neural network architectures.
  • Prior teaching or mentoring experience in computer science or data analytics.
  • Publications or presentations at scientific conferences.

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