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Machine Learning Object Detection Jobs in California

XPENG

Staff Machine Learning Engineer

Santa Clara, CA · On-site

About the Role We are looking for a strong Machine Learning Engineer / Computer Vision Engineer to ... Solid understanding of object detection training workflows, including dataset preparation ...

XPENG

Staff Machine Learning Engineer

Santa Clara, CA · On-site

About the Role We are looking for a strong Machine Learning Engineer / Computer Vision Engineer to ... Solid understanding of object detection training workflows, including dataset preparation ...

FieldAI

2.53 3D Machine Learning Engineer

Irvine, CA · On-site

Responsibilities : • Design and implement scalable machine learning pipelines for large-scale 3D spatial data processing for point cloud analysis, object detection, segmentation, and scene ...

shefsolutionsllc

Data Science And Ai

San Francisco, CA · On-site

$120 - $160/hr

... anomaly detection using machine learning techniques. Nice to Have * Experience working at a startup. * Experience with real‑time video analysis, object detection, and scene understanding.

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Machine Learning Object Detection information

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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Machine Learning Object Detection jobs near you

Data Scientist - Computer Vision

SPAR Information Systems LLC

Santa Clara, CA • On-site

Contractor

Re-posted 22 hours ago

Job description

Client Job Description: Title: Data Scientist -- Computer Vision
Location: Onsite – Santa Clara, CA
Job Description/ Important details:
1. Solid knowledge of image processing: Filtering, Binary Morphology, Perspective / Affine transformation, Edge Detection
2. Machine Learning: Regression, Supervised and Unsupervised Learning,
3. Knowledge of HDR and Deep Learning object detection.
Job Description:
Additional Sills: Machine Learning,Regression,Binary,Pca