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Weekend Machine Vision Engineer Jobs in California

Pano

Computer Vision Engineer

San Francisco, CA · On-site +1

$141K - $184K/yr

  • Medical

  • Retirement

  • PTO

Help implement and maintain machine learning and computer vision pipelines. * Assist with deploying ... Document experiments, engineering decisions, and best practices. * Take on a variety of technical ...

Meta

Computer Vision Engineer

Burlingame, CA · On-site

$125K - $148K/yr

Meta Reality Labs is seeking a Machine Learning Engineer to drive the productization of gesture recognition models for our AR/VR devices. This role brid.

Cesna Group

Junior Computer Vision Engineer

San Diego, CA · On-site

$100K - $200K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Job Summary * - To research and develop scalable computer vision and machine learning solutions to ... Master's degree in Computer Science or Electrical Engineering plus 2 or more years of relevant ...

Archer

Computer Vision Engineer

San Jose, CA

$140K - $260K/yr

Strong background in computer vision and/or machine learning, with a degree in a related technical field or equivalent experience * Proficiency in C++ and Python * Experience with deep-learning ...

Archer

Computer Vision Engineer

San Jose, CA · On-site

$140K - $260K/yr

Strong background in computer vision and/or machine learning, with a degree in a related technical field or equivalent experience * Proficiency in C++ and Python * Experience with deep-learning ...

Apex Informatics

Computer Vision Engineer V

Sunnyvale, CA · On-site

$132K - $156K/yr

Top Skill need solid DSP SW Engineer with recent exp in CV Minimum Qualifications: • Bachelor ... machine learning, and image processing, or ISP sensors. • Experience with low-level SW ...

Pano

Senior Computer Vision Engineer

San Francisco, CA · On-site +1

$195K - $255K/yr

  • Medical

  • Retirement

  • PTO

MS or PhD in Computer Science, Electrical Engineering, Robotics, or a related field. * 5+ years of industry experience in computer vision or machine learning. * Strong experience with PyTorch and ...

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All JobsMachine Vision Engineer JobsWeekend Machine Vision Engineer JobsWeekend Machine Vision Engineer Jobs in California

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 cities in California are hiring for Weekend Machine Vision Engineer jobs?

Cities in California with the most Weekend Machine Vision Engineer job openings:

Weekend Machine Vision Engineer jobs near you

Computer Vision Engineer

Pano

San Francisco, CA • On-site, Remote

$141K - $184K/yr

Full-time

Medical, Retirement, PTO

Posted 11 days ago

Job description

Help us tackle the growing wildfire crisis with the latest advancements in AI and IoT
Who we are
The challenge: Every minute matters in wildfire response. As climate change increases the frequency and intensity of wildfires-with longer fire seasons, drier fuels, and more extreme weather-new ignitions can spread rapidly, putting communities, critical infrastructure, and ecosystems at risk. Today, many wildfires are first reported by members of the public, meaning it can take valuable time to detect a fire, confirm its location and size, and mobilize responders. Fire agencies need faster, more reliable ways to detect, verify, and pinpoint new ignitions so they can respond quickly and prevent small fires from becoming catastrophic events.
About Pano AI: Pano AI is the leader in AI-powered wildfire detection and intelligence, helping fire professionals detect, respond to, and contain wildfires faster and more safely. Our platform combines advanced hardware, software, artificial intelligence, satellite imagery, and other data sources to provide real-time situational awareness and actionable intelligence. Using a network of ultra-high-definition, 360-degree cameras positioned across high vantage points, Pano AI delivers a real-time view of wildfire activity, enabling faster, more informed decision-making when every second counts.
We are a team of more than 175 people working in a hybrid-remote environment across North America and Australia, with headquarters in San Francisco. Our customers include government agencies, utilities, insurers, and private landowners who rely on Pano AI to help protect people, property, and natural landscapes. Pano AI currently serves customers across the United States, Australia, and Canada, monitoring more than 50 million acres worldwide.
Our work has been recognized by Fast Company as one of the Top 10 Most Innovative AI Companies in 2023 and one of the World's Most Innovative Companies in 2026, ranking #1 in Sustainability. We have also been named to TIME's list of the 100 Most Influential Companies of 2025 and recognized by MIT Technology Review as one of the top climate technology companies to watch.
Backed by $89 million in funding from leading investors including Giant Ventures, Liberty Mutual Ventures, Tokio Marine Future Fund, Congruent Ventures, Initialized Capital, Salesforce Ventures, and T-Mobile Ventures, we're building technology that helps communities around the world become more resilient to wildfire. Learn more at www.pano.ai.
The Role
We are looking for a motivated Computer Vision Engineer to help build the next generation of cloud/edge-based vision systems for wildfire detection and environmental monitoring.
In this role, you will work alongside experienced AI researchers and engineers to develop, evaluate, optimize, and deploy computer vision models on both cloud and edge devices. You will gain hands-on experience across modern computer vision, edge AI, embedded systems, and real-world AI deployment.
Beyond wildfire detection, you will contribute to a variety of computer vision projects, including vegetation detection, asset recognition, instance segmentation, scene understanding, and spatial reasoning. We value curiosity, adaptability, and a willingness to learn new technologies and tackle diverse technical challenges as our products evolve.
This is an excellent opportunity for an engineer who enjoys learning across the entire AI stack and wants to grow into a senior technical contributor.
What you'll do
  • Assist in developing computer vision models for:
    • Wildfire smoke detection
    • Vegetation detection and classification
    • Asset detection and recognition
    • Instance and semantic segmentation
    • Scene understanding and spatial reasoning
  • Help implement and maintain machine learning and computer vision pipelines.
  • Assist with deploying and optimizing AI models on NVIDIA Jetson and other edge platforms.
  • Support model optimization efforts, including TensorRT conversion, quantization, and inference acceleration.
  • Build tools for data processing, visualization, benchmarking, evaluation, and monitoring.
  • Conduct experiments, analyze model performance, and present findings to the team.
  • Debug inference, deployment, networking, and hardware integration issues.
  • Contribute to continuous learning, model evaluation, and data quality improvement workflows.
  • Collaborate closely with AI researchers, software engineers, hardware engineers, and product teams.
  • Document experiments, engineering decisions, and best practices.
  • Take on a variety of technical challenges as needed and continuously expand your skills across computer vision and cloud/edge AI.

What you'll bring
Required
  • BS or MS in Computer Science, Electrical Engineering, Robotics, or a related field.
  • 1-3 years of experience (including internships or research) in software engineering, machine learning, or computer vision.
  • Experience with Python and deep learning frameworks such as PyTorch.
  • Understanding of machine learning fundamentals and modern computer vision techniques.
  • Familiarity with Linux development environments.
  • Strong problem-solving skills, curiosity, and a desire to learn.
  • Excellent communication and teamwork skills.

Preferred
  • Experience with NVIDIA Jetson, CUDA, TensorRT, ONNX, or embedded AI platforms.
  • Experience with OpenCV.
  • Experience with one or more of the following:
    • Object detection
    • Instance or semantic segmentation
    • Image classification
    • Multi-object tracking
    • Video understanding
  • Familiarity with vision foundation models such as SAM, Grounding DINO, or DINO is a plus.
  • Experience with cloud platforms, MLOps, or CI/CD workflows.
  • Interest in deploying AI systems in real-world environments, particularly outdoor vision systems.

Final compensation for regular full-time employees is determined by a variety of factors, including job-related qualifications, education, experience, skills, knowledge, and geographic location. In addition to base salary, regular full-time roles are eligible for equity. Benefits are tailored to local market standards and statutory requirements in the employee's country of employment, and may include health coverage, retirement or pension contributions, and paid time off. Specific benefit details will be shared during the interview process.

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