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Weekend Machine Vision Engineer Jobs in California

Sr. Machine Learning Engineer

San Mateo, CA

$63.50 - $84/hr

Leverage big data tools and programming frameworks to ensure that the raw data gathered from data ... Prior experience with machine vision and machine learning in financial services is essential. Key ...

In this role at Dexterity, you will be working on writing Computer Vision code and building Machine Learning models for computer vision. The role will involve understanding our current systems and ...

Come join our high performing team consisting of PhDs, machine vision and algorithm engineers building the next generation of AI enabled semiconductor inspection equipment. The successful candidate ...

Algorithm Engineer

Milpitas, CA · On-site

$136K - $231K/yr

Come join our high performing team consisting of PhDs, machine vision and algorithm engineers building the next generation of AI enabled semiconductor inspection equipment. The successful candidate ...

Deep understanding of machine learning principles and methodologies * Experience with implementing ... Experience with 3D Vision * Publication record in relevant venues (CVPR, ICLR, ICCV, ECCV, NeurIPS ...

Come join our high performing team consisting of PhDs, machine vision and algorithm engineers building the next generation of AI enabled semiconductor inspection equipment. The successful candidate ...

Deep understanding of machine learning principles and methodologies * Experience with implementing ... Experience with 3D Vision * Publication record in relevant venues (CVPR, ICLR, ICCV, ECCV, NeurIPS ...

Come join our high performing team consisting of PhDs, machine vision and algorithm engineers building the next generation of AI enabled semiconductor inspection equipment. The successful candidate ...

Come join our high performing team consisting of PhDs, machine vision and algorithm engineers building the next generation of AI enabled semiconductor inspection equipment. The successful candidate ...

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Weekend Machine Vision Engineer information

What is the difference between Weekend Machine Vision Engineer vs Weekend Robotics Technician?

AspectWeekend Machine Vision EngineerWeekend Robotics Technician
Required CredentialsBachelor's in Engineering, Computer Science, or related field; knowledge of image processing and programmingAssociate's or Bachelor's in Robotics, Electronics, or related field; hands-on technical skills
Work EnvironmentTech labs, manufacturing facilities, or research centers focusing on vision systemsManufacturing floors, maintenance workshops, or field service settings
Industry UsageManufacturing, automation, quality controlManufacturing, assembly lines, equipment maintenance

The Weekend Machine Vision Engineer primarily focuses on developing and implementing vision systems for automation and quality control, requiring programming and image processing skills. In contrast, the Weekend Robotics Technician handles maintenance and troubleshooting of robotic systems, emphasizing hands-on technical skills. Both roles are essential in manufacturing environments but differ in their focus and daily tasks.

What are the key skills and qualifications needed to thrive as a Weekend Machine Vision Engineer, and why are they important?

To excel as a Weekend Machine Vision Engineer, you typically need a background in computer vision, image processing, and a degree in engineering, computer science, or a related field. Familiarity with programming languages like Python or C++, experience with machine vision libraries (such as OpenCV or Halcon), and knowledge of industrial camera systems are commonly required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for this role. These competencies ensure the development and maintenance of reliable vision systems that support high-quality automation and manufacturing processes during critical weekend operations.

What does a Weekend Machine Vision Engineer do?

A Weekend Machine Vision Engineer is responsible for developing, testing, and maintaining computer vision systems that enable machines to interpret and process visual data. This role typically involves working weekends to support production lines or R&D projects that need ongoing monitoring and updates outside of standard business hours. Key tasks include programming vision algorithms, integrating cameras and sensors, troubleshooting system issues, and collaborating with other engineers to improve automation and quality control processes. Weekend Machine Vision Engineers are commonly found in manufacturing, robotics, and quality assurance environments that require continuous technical support.

What are some common challenges faced by a Weekend Machine Vision Engineer, and how can they be addressed?

As a Weekend Machine Vision Engineer, you may encounter challenges such as troubleshooting unexpected equipment malfunctions, adapting to rapidly changing production needs, and working with limited on-site support compared to weekday shifts. To address these, it's important to develop strong problem-solving skills, stay up-to-date with the latest software and hardware updates, and maintain clear documentation for seamless communication with weekday teams. Proactively coordinating with colleagues during shift handovers and leveraging remote support resources can also help ensure smooth operations and minimize downtime.
What are the most commonly searched types of Machine Vision Engineer jobs in California? The most popular types of Machine Vision Engineer jobs in California are:
What cities in California are hiring for Weekend Machine Vision Engineer jobs? Cities in California with the most Weekend Machine Vision Engineer job openings:

Research Robotics/Computer Vision Engineer

Skild AI

San Mateo, CA • On-site

Full-time

Posted 3 days ago


Job description

Job Summary:
Skild AI is building the world's first general purpose robotic intelligence, focusing on data-driven machine learning for robotics deployment. They seek a Research Robotics/Computer Vision Engineer responsible for developing intelligent robotic systems, with a focus on 3D computer vision and autonomous navigation.
Responsibilities:
• (i) implementing perception on robots to enable safe exploration and navigation in real world environments in collaboration with the locomotion team
• (ii) reconstructing an entire scene in 3D using monocular images, estimating camera poses, optimizing and streamlining 3D SLAM
• (iii) developing a set of software tools for localization of a robot using only visual inputs
• (iv) building robust software to enable life-long mapping on a robot via optimally merged pose-graphs
• (v) visual servoing wrt objects detected/ tracked to control robot motion
• (vi) researching novel techniques to detect and cater to glare during robotic mapping and navigation
• (vii) building infrastructure and pipeline and collecting data to enable streaming of hand movements for training robot manipulation tasks such as pick and place
• (viii) maintaining a camera and 2D lidar based navigation stack, including fixing bugs, adding new customer feature requests, and ensuring successful deployments.
Qualifications:
Required:
• Must have a master's degree (or foreign equivalent) in Computer Vision, Robotics, or a directly related discipline and one (1) year of experience in Machine Learning or Data Science.
• Must have any experience with or knowledge of each of the following: (i) reconstructing 3D scenes using monocular videos, meshes, pointclouds, Neural Radiance Fields, and Gaussian Splats; (ii) reconstructing rigid and articulated hand-held objects from videos, including inferring the time-varying hand configurations and relative poses of the objects; (iii) using generative computer vision, including diffusion models to guide reconstruction, or addressing occlusion and limited viewpoint variations in videos via data driven priors; (iv) optimizing attention-based models for perception used in autonomous navigation systems; (v) using Neural Architectural Search (NAS) to find better perception backbone architectures with higher accuracies and lower latencies; and (vi) cloud-based training in AWS, Google cloud, or Vetex AI and optimized data loading for cloud based distributed training for deep learning workloads (e.g. Pytorch dataloader, or sharding) with hardware-in-loop.
Company:
Building general purpose robotic intelligence. Founded in 2023, the company is headquartered in Pittsburgh, Pennsylvania, US, , with a team of 11-50 employees. The company is currently Early Stage.