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Machine Learning Object Detection Jobs (NOW HIRING)

... 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 ...

Machine Learning Engineer

Frisco, TX · On-site

$140 - $190/hr

Fine‑tune and deploy computer vision and deep learning models for object detection, object ... Contribute to our machine learning repositories and optimize models for performance, scalability ...

Advance core computer vision model performance (object detection, segmentation, OCR) for warehouse ... MS or PhD in Computer Science, Machine Learning, Robotics, or a related field Nice to Have

As an AI & Machine Learning Engineer, you will design, build, and deploy the intelligent systems ... Develop deep learning pipelines for object detection, segmentation, and pose estimation * Build ...

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Machine Learning Object Detection information

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$31.5K

$128.8K

$193.5K

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

As of Sep 1, 2026, the average yearly pay for machine learning object detection in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

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 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 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.
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What cities are hiring for Machine Learning Object Detection jobs?

Cities with the most Machine Learning Object Detection job openings:

What states have the most Machine Learning Object Detection jobs?

States with the most job openings for Machine Learning Object Detection jobs include:

Infographic showing various Machine Learning Object Detection job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Principal Machine Learning Scientist

Pittsburgh, PA • On-site

Gather AI
Industrial Automation Equipment Manufacturing • 11 - 50 employees

Full-time

Re-posted yesterday


Job description

Job Summary:
Gather AI is pioneering a new era of warehouse intelligence with its vision-powered platform that utilizes autonomous drones for real-time data capture. They are seeking a Principal Machine Learning Scientist to enhance their computer vision systems for warehouse inventory scanning, focusing on the full ML lifecycle to achieve significant business outcomes.
Responsibilities:
• Advance core computer vision model performance (object detection, segmentation, OCR) for warehouse inventory scanning across drone and MHE Vision platforms
• Own the full ML lifecycle from research and experiment design through production deployment and monitoring — applying rigorous ablation studies and SOTA methodology
• Collaborate with the ML infrastructure team on model optimization and deployment across cloud and edge inference targets (ONNX, TensorRT, quantization)
• Work with Operations and Product to understand customer needs and translate them into ML improvements with measurable business impact
• Provide technical leadership and mentorship to the ML team, raising standards for experiment design, model evaluation, and production readiness
• Explore next-generation perception capabilities, including embedded and on-prem inference optimization for new deployment targets
Qualifications:
Required:
• 10+ years of experience in machine learning or computer vision
• Deep expertise in CNNs, object detection, image segmentation, and OCR using PyTorch (preferred) or TensorFlow
• Strong Python proficiency and software engineering fundamentals; hands-on experience with OpenCV and GPU computing
• Track record of delivering production ML systems at scale, including model training, evaluation, and deployment
• MS or PhD in Computer Science, Machine Learning, Robotics, or a related field
Preferred:
• Experience with drone, robotics, or autonomous systems perception
• Publications in top vision or robotics conferences (CVPR, ICCV, ICRA, NeurIPS, CoRL)
• Experience designing and deploying models for real-time inference on constrained compute platforms
• Warehouse, logistics, or supply chain domain experience
Company:
We deliver the foundational intelligence layer for the intralogistics industry. Founded in 2017, the company is headquartered in Pittsburgh, USA, with a team of 51-200 employees. The company is currently Growth Stage.