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Machine Learning Object Detection Jobs in Raleigh, NC

... object detection networks (e.g., YOLO, CenterNet) and modern image classification techniques • Software expertise: Python and associated numerical and analytics packages (NUMPY, PANDAS, etc.); git;

Applicants are ideally familiar with computer vision algorithms like object detection networks (e.g ... Machine learning fundamentals; Deep knowledge of state-of-the-art in any of the following: computer ...

This team is investing in machine learning and analytics capabilities to help improve fraud detection, predictive insights, and operational decision-making across customer-facing products. This is an ...

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:

You will also be involved in developing and testing and solutions in strategically and tactically significant applications and use cases, including file protocols, machine learning, object storage ...

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Machine Learning Object Detection information

See Raleigh, NC salary details

$30.6K

$125.2K

$188.1K

How much do machine learning object detection jobs pay per year?

As of May 31, 2026, the average yearly pay for machine learning object detection in Raleigh, NC is $125,174.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,700.00 and $150,700.00 per year, depending on experience, location, and employer.

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 Raleigh, NC? For Machine Learning Object Detection jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Machine Learning Object Detection jobs in Raleigh, NC look for? The top searched job categories for Machine Learning Object Detection jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Machine Learning Object Detection jobs? Cities near Raleigh, NC with the most Machine Learning Object Detection job openings:

Machine Learning Engineer

CoVar

Durham, NC • On-site

Full-time

Posted 13 days ago


Job description

Job Summary:
CoVar is a small AI/ML R&D software company in Durham, NC, that uses artificial intelligence to solve problems that matter. In this role, you will help develop software and machine learning algorithms to address real-world customer challenges, working closely with data and presenting your findings to high-level customers.
Responsibilities:
• help CoVar develop software and machine learning algorithms to solve real-world customer problems
• work with data, develop algorithms, evaluate results, and write the production code that goes onto real-world systems
• present your work to high-level customers in the DoD and in the industry
• opportunities to publish novel work in both classified and unclassified settings.
Qualifications:
Required:
• Expertise in Python (including NumPy, pandas, and other packages)
• Experience with either PyTorch or TensorFlow
• Deep understanding of machine learning fundamentals (gradient descent, cross-validation, ROC curves, confusion matrices)
• Knowledge of classical machine learning (e.g., support-vector-machines, logistic regression)
• Familiarity with computer vision algorithms like object detection networks (e.g., YOLO, CenterNet) and modern image classification techniques
• Software expertise: Python and associated numerical and analytics packages (NUMPY, PANDAS, etc.); git; PYTORCH or TensorFlow; CI/CD pipelines and regression testing
• AI/ML expertise: Machine learning fundamentals; Deep knowledge of state-of-the-art in any of the following: computer vision (preferred), natural language processing, classical machine learning, Bayesian models, etc.
• B.S., preferably M.S. or Ph.D in engineering, math, computer science, or related field
• Excellent technical communication skills
• Ability to work in Durham, NC (relocation assistance available)
• Eligibility for US security clearance (US citizenship is required)
Preferred:
• Previous experience with DoD customers
• Department of Defense project experience
• Active US security clearance (secret or higher)
Company:
CoVar is a leader in machine learning and artificial intelligence solutions. Founded in 2011, the company is headquartered in Mclean, USA, with a team of 11-50 employees. The company is currently Early Stage.