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Machine Learning Object Detection Jobs in California

Intuitive

Staff Machine Learning Engineer

Sunnyvale, CA · On-site

As a Staff Machine Learning Engineer, you will lead the design and development of perception and ... object detection, and/or instance segmentation. Strong familiarity with modern vision architectures.

Intuitive

Staff Machine Learning Engineer

Sunnyvale, CA · On-site

As a Staff Machine Learning Engineer, you will lead the design and development of perception and ... object detection, and/or instance segmentation. Strong familiarity with modern vision architectures.

Nvidia

Senior Machine Learning Engineer

Santa Clara, CA · On-site

$143K - $189K/yr

Design, train, and optimize innovative machine learning models for LiDAR/camera perception and multi-sensor fusion (e.g., object detection/classification, image classification, semantic segmentation ...

Nvidia

Senior Machine Learning Engineer

Santa Clara, CA

$143K - $189K/yr

Design, train, and optimize innovative machine learning models for LiDAR/camera perception and multi-sensor fusion (e.g., object detection/classification, image classification, semantic segmentation ...

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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.

What are popular job titles related to Machine Learning Object Detection jobs in California?

For Machine Learning Object Detection jobs in California, the most frequently searched job titles are:

What job categories do people searching Machine Learning Object Detection jobs in California look for?

The top searched job categories for Machine Learning Object Detection jobs in California are:

What cities in California are hiring for Machine Learning Object Detection jobs?

Cities in California with the most Machine Learning Object Detection job openings:

Machine Learning Object Detection jobs near you

Staff Software Engineer - Machine Learning

San Francisco, CA • On-site

Hivemapper
Internet and IT • 11 - 50 employees
Learn more about Hivemapperexternal

Full-time

Re-posted 25 days ago

Job description

Job Summary:
Hivemapper is a decentralized global mapping data network built by tens of thousands of people. They are seeking a Staff Software Engineer to help shape the computer vision strategy and integrate machine learning solutions into production systems.
Responsibilities:
• Help shape the CV strategy touching the full mapping stack, all the way from hardware to data insights
• Balance the state of the art and bleeding edge with practicality; produce production-grade ML solutions trained on a huge corpus of standardized data that are efficient w.r.t cost and performance
• Integrate ML solutions with our production systems; at the edge and in large offline clusters
Qualifications:
Required:
• Demonstrated expertise in building ML solutions, including training and deploying models, as well as integrating them into production software systems
• Hands-on experience with Image Processing and Computer Vision: Object Detection, Classification, Tracking, Localization, 3D Reconstruction, Vector embeddings, etc.
• Hands-on experience with general ML and Data Mining: Clustering, Predictions, Unsupervised Methods, Ensemble Methods, Graph Optimization, etc.
• Hands on experience with 3D reconstruction pipelines (either monocular or stereo)
• Strong programming and applied math skills (linear algebra, statistics, multivariate optimization)
• Strong software engineering fundamentals
Preferred:
• PhD in Computer Vision or related field
• Knowledge of distributed compute systems like Hadoop/Spark
• Experience with a variety of different ML frameworks (PyTorch, TensorFlow, OpenVINO, ONNX, etc.)
Company:
Hivemapper is a community-owned mapping network that creates unprecedented coverage, freshness, and quality. Founded in 2015, the company is headquartered in San Francisco, USA, with a team of 11-50 employees. The company is currently Early Stage.

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