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Computer Vision Machine Learning Jobs (NOW HIRING)

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Computer Vision Engineer

Burlingame, CA

$183K/yr

RL has global departments dedicated to research and development in computer vision, machine learning, haptics, social interaction, and more. RL is committed to driving the state of the art forward ...

Meta

Computer Vision Engineer

Redmond, WA

$183K/yr

RL has global departments dedicated to research and development in computer vision, machine learning, haptics, social interaction, and more. RL is committed to driving the state of the art forward ...

Meta

Computer Vision Engineer

Sunnyvale, CA

$183K/yr

RL has global departments dedicated to research and development in computer vision, machine learning, haptics, social interaction, and more. RL is committed to driving the state of the art forward ...

Meta

Computer Vision Engineer

Seattle, WA

$183K/yr

RL has global departments dedicated to research and development in computer vision, machine learning, haptics, social interaction, and more. RL is committed to driving the state of the art forward ...

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Computer Vision Machine Learning information

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How much do computer vision machine learning jobs pay per hour?

As of Jul 11, 2026, the average hourly pay for computer vision machine learning in the United States is $19.92, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $21.88 per hour, depending on experience, location, and employer.

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

To thrive as a Computer Vision Machine Learning Engineer, you need strong foundations in mathematics, programming (especially Python or C++), and expertise in machine learning algorithms, typically supported by a degree in computer science, engineering, or a related field. Familiarity with deep learning frameworks like TensorFlow or PyTorch and experience with image processing libraries are essential, along with knowledge of version control systems. Strong problem-solving, collaboration, and communication skills help you translate complex requirements into effective models and work efficiently in multidisciplinary teams. These skills ensure the development of robust computer vision solutions that address real-world challenges and drive innovation.

What are some common challenges faced by Computer Vision Machine Learning engineers when deploying models to production environments?

Computer Vision Machine Learning engineers often encounter challenges such as ensuring models perform well on real-world, diverse image data that may differ from training datasets. Managing computational efficiency and latency is crucial, especially for real-time applications. Additionally, integrating models with existing software systems and maintaining accuracy as data evolves can be complex. Collaboration with data engineers, software developers, and product teams is essential to address these challenges and ensure smooth deployment and monitoring.

What is the difference between Computer Vision Machine Learning vs Data Scientist?

AspectComputer Vision Machine LearningData Scientist
Required CredentialsBachelor's or higher in CS, ML, or related; experience with ML frameworksBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentResearch labs, tech companies, AI startups focusing on visual dataBusiness, finance, healthcare sectors analyzing diverse data sets
Industry UsageDeveloping visual recognition systems, image processingData analysis, predictive modeling, business insights
Common Search/ComparisonYesYes

While both roles involve machine learning, Computer Vision Machine Learning specializes in visual data and image processing, whereas Data Scientists work with a broader range of data types to generate insights across various industries.

What is a Computer Vision Machine Learning Engineer?

A Computer Vision Machine Learning Engineer is a professional who develops algorithms and models that enable computers to interpret and understand visual data from the world, such as images and videos. They use techniques from machine learning, deep learning, and image processing to build systems capable of tasks like object detection, image classification, facial recognition, and scene understanding. Their work is critical in fields such as autonomous vehicles, healthcare imaging, security, and augmented reality. These engineers typically have strong skills in programming, mathematics, and data analysis, and often work closely with data scientists and software developers.
More about Computer Vision Machine Learning jobs
What cities are hiring for Computer Vision Machine Learning jobs? Cities with the most Computer Vision Machine Learning job openings:
What states have the most Computer Vision Machine Learning jobs? States with the most job openings for Computer Vision Machine Learning jobs include:
What job categories do people searching Computer Vision Machine Learning jobs look for? The top searched job categories for Computer Vision Machine Learning jobs are:
Computer Vision Machine Learning jobs near you
Infographic showing various Computer Vision Machine Learning job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 85% Full Time, 12% Part Time, and 2% Contract. Highlights an 82% Physical, 1% Hybrid, and 17% Remote job distribution, with an average salary of $41,429 per year, or $19.9 per hour.
Sr. Computer Vision / Machine Learning Engineer

Sr. Computer Vision / Machine Learning Engineer

Corvus Robotics

Mountain View, CA • On-site

$144K - $190K/yr

Full-time

Posted 28 days ago

Job description

About the company
Every physical good spends time in a warehouse, and every warehouse tracks their inventory. Today, nearly 100% of warehouses track their inventory manually using barcode scanners and climbing forklifts.
We're Corvus Robotics. Our fully autonomous Corvus One™ drones use computer vision & robotics to automatically track inventory, improving worker safety and increasing labor efficiency. We believe that data-driven, safe inventory management will optimize the global physical economy and improve economic prosperity for humanity.
About the role
We are hiring Computer Vision / Machine Learning Software Engineers to build compute-constrained models for deployed robots. You'll tackle diverse technical challenges, working with vast amounts of sensor data to increase environmental awareness and provide customers with deeper inventory insights. We value problem-solving, innovation, and continuous learning, and we encourage exploring new technologies to advance our machine learning capabilities.
What you'll do
  • Develop solutions for advanced computer vision tasks, including:
    • Monocular and stereo depth estimation
    • Learning-based structure-from-motion
    • 3D occupancy networks
    • Scene understanding
    • Object detection
  • Optimize performance, accuracy, and speed of compute-constrained models
  • Collaborate across teams to deploy CV/ML models into production
  • Improve ML pipelines and infrastructure for dataset management, training, and deployment
  • Participate in R&D initiatives (20% of time) to experiment with state-of-the-art techniques
  • Drive business value by leveraging your work across robotics, software, and deployment teams

This role is in-person hybrid in Mountain View, CA. US work authorization is preferred but not required, can sponsor visas.
Must have
  • 5+ years of industry experience in Computer Vision / Machine Learning, Python/PyTorch
  • Expertise in 2D and 3D computer vision techniques
  • Proficiency with Linux, Git, AWS/GCP, and CI/CD workflows
  • Experience in performance engineering for deep neural networks (both training and inference)
  • Knowledge of model optimization techniques for embedded systems, including knowledge distillation, model quantization, and network pruning
  • Adaptive and desire to assume responsibility in a fast-paced startup environment
Nice to have
  • Experience with C/C++
  • Familiarity with ROS (Robot Operating System)
  • Knowledge of model deployment frameworks (e.g., TensorRT, RKNN, OpenVINO, ONNX, CoreML)
  • Experience with TypeScript/JavaScript and Django
  • Experience with data labelers, tooling, and data management

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