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Computer Vision Engineering Jobs (NOW HIRING)

Computer Vision Engineer

Bellevue, WA · On-site

$125K - $147K/yr

Role Overview We are seeking a highly skilled and innovative Computer Vision Engineering to lead the lifecycle of complex cross-functional projects within our North America Fulfillment Network. This ...

Computer Vision Engineer

San Diego, CA · On-site

$112K - $130K/yr

Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or related field. * 3-5+ years of experience in computer vision, preferably in a real-time, product ...

Computer Vision Engineer

San Diego, CA · On-site

$118K - $139K/yr

Engineering Group, Engineering Group > Video Systems, HW Architecture General Summary: Qualcomm's Computer Vision Systems team is building the intelligence behind the world's most advanced Snapdragon ...

Computer Vision Engineer

Bellevue, WA

$125K - $148K/yr

Role Overview We are seeking a highly skilled and innovative Computer Vision Engineering to lead the lifecycle of complex cross-functional projects within our North America Fulfillment Network. This ...

Computer Vision Engineer

San Diego, CA · On-site

$112K - $130K/yr

Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or related field. * 3-5+ years of experience in computer vision, preferably in a real-time, product ...

Computer Vision Engineer

Sterling, VA · On-site

$110K - $130K/yr

As a Computer Vision Engineer, you will: * Drive the architecture, development, and deployment of advanced 2D and 3D computer vision systems that enable Molg's robotic microfactories. * Own the full ...

Computer Vision Engineer

Grapevine, TX · On-site

$103K - $121K/yr

... engineering solutions. The role involves developing real-time computer vision models, participating in software application design, and ensuring software quality through testing and code reviews.

Computer Vision Engineer

Costa Mesa, CA · On-site

$191K - $253K/yr

This role requires not only technical expertise in computer vision and robotics but also the ability to make pragmatic engineering tradeoffs, considering the unique constraints of aerial platforms.

Computer Vision Engineer

San Diego, CA · On-site

$118K - $139K/yr

Required : • Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or related field. • 3-5+ years of experience in computer vision, preferably in a real ...

The Director of Computer Vision will drive the technical vision, research and engineering execution ... Technical Vision, Engineering Leadership, and Execution: Provide executive technical leadership to ...

Computer Vision Engineer

Sterling, VA

$110K - $130K/yr

As a Computer Vision Engineer, you will be responsible for: * Continuous design, development, testing, and deployment of 2D and 3D vision capabilities incorporated into the Molg Microfactories.

The Director of Computer Vision will drive the technical vision, research and engineering execution ... Technical Vision, Engineering Leadership, and Execution: Provide executive technical leadership to ...

The Director of Computer Vision will drive the technical vision, research and engineering execution ... Technical Vision, Engineering Leadership, and Execution: Provide executive technical leadership to ...

The Director of Computer Vision will drive the technical vision, research and engineering execution ... Technical Vision, Engineering Leadership, and Execution: Provide executive technical leadership to ...

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Computer Vision Engineering information

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$48.5K

$121.5K

$137.5K

How much do computer vision engineering jobs pay per year?

As of Jun 10, 2026, the average yearly pay for computer vision engineering in the United States is $121,515.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,500.00 and $131,500.00 per year, depending on experience, location, and employer.

What is the difference between Computer Vision Engineering vs Machine Learning Engineering?

AspectComputer Vision EngineeringMachine Learning Engineering
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; knowledge of image processing and computer vision librariesBachelor's or Master's in Computer Science, Data Science, or related fields; strong programming and statistical skills
Work EnvironmentDeveloping algorithms for image/video analysis, object detection, and scene understandingBuilding models for various data types, including images, text, and tabular data
Employer & Industry UsageTech companies, robotics, automotive, healthcare, securityTech firms, finance, healthcare, e-commerce, research institutions

Computer Vision Engineering focuses on developing algorithms for interpreting visual data, while Machine Learning Engineering covers a broader range of data types and applications. Both roles require strong programming skills and often overlap in skills and tools, but their primary focus and industry applications differ.

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

To thrive as a Computer Vision Engineer, you need a solid background in mathematics, programming (especially Python or C++), and machine learning, typically backed by a degree in computer science or a related field. Familiarity with tools such as OpenCV, TensorFlow, PyTorch, and experience with image processing libraries and deep learning frameworks is essential. Strong problem-solving skills, attention to detail, and effective communication set standout professionals apart in this field. These skills and qualities are crucial for developing innovative computer vision solutions and collaborating across multidisciplinary teams to solve complex visual recognition challenges.

What is computer vision engineering?

Computer vision engineering is a field within artificial intelligence that focuses on enabling computers and systems to interpret and process visual information from the world, such as images and videos. Computer vision engineers develop algorithms and models that allow machines to identify, classify, and analyze visual data, often for applications like facial recognition, autonomous vehicles, medical imaging, and industrial automation. They work with large datasets, deep learning frameworks, and various programming languages to build and optimize these intelligent systems.

What are the typical challenges faced by Computer Vision Engineers when deploying models to production environments?

Computer Vision Engineers often encounter challenges such as ensuring models perform accurately on real-world data, optimizing inference speed for deployment on various hardware, and managing large-scale image or video data pipelines. Additionally, integrating computer vision solutions with existing backend systems and maintaining model performance as data evolves can be complex. Collaboration with data engineers, software developers, and QA teams is essential to address these issues and ensure robust, scalable deployment.
More about Computer Vision Engineering jobs
Infographic showing various Computer Vision Engineering job openings in the United States as of June 2026, with employment types broken down into 3% As Needed, 52% Full Time, 44% Part Time, and 1% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $121,515 per year, or $58.4 per hour.
Computer Vision Engineer

Computer Vision Engineer

SID Global Solutions

Bellevue, WA • On-site

$125K - $147K/yr

Full-time

Posted 5 days ago


Job description

Job Description
Role Overview
We are seeking a highly skilled and innovative Computer Vision Engineering to lead the lifecycle of complex cross-functional projects within our North America Fulfillment Network. This role focuses on designing, developing, and implementing advanced engineering solutions, integrating IIoT hardware, computer vision, and machine learning to improve material handling, operator workflows, and fulfillment processes.
The ideal candidate has a strong background in engineering design, computer vision, and applied machine learning, with proven experience driving large-scale projects, collaborating across teams, and delivering impactful outcomes in dynamic operational environments.
Key Responsibilities
  • Lead and manage end-to-end life cycles ofcomplex cross-functional projects spanning organizations and geographies,ensuring delivery of impactful business outcomes.
  • Engineering Solutions: Design and develop engineering solutions formaterial handling challenges, considering human-equipment interactions andoperational excellence.
  • IIoT Development: Develop, configure, and implement IIoThardware to enhance equipment, processes, and operator workflows.
  • Simulation & Modeling: Collaborate with Scientists to createadvanced simulation models and perform "what-if" scenario testing to driveoptimal hardware and process solutions.
  • Concept & Design Leadership: Lead concept efforts for optimal solutionsincluding equipment specifications, material flow, ergonomics, associateexperience, operational considerations, and site layout.
  • Vendor & Stakeholder Collaboration: Partner with suppliers, vendors, andinternal teams to deliver innovative solutions with scalability andefficiency.
  • Documentation & Standards: Ensure all solutions are documented withSOPs and/or structured change control, setting standards for engineeringexcellence.
  • Multi-Project Management: Manage multiple initiatives simultaneouslywhile influencing, negotiating, and communicating effectively withinternal and external stakeholders.
  • Thought Leadership: Deliver artifacts (research, schematics,prototypes, 3D models, analysis, test plans, narratives) that setbenchmarks for organizational engineering standards.
  • Consensus Building: Communicate complex ideas clearly, harmonizediverse perspectives, and build consensus to resolve contentious issues.

Must-Have Qualifications
  • Proven experience in computer vision (CV)and machine learning (ML) integration for real-time solutions.
  • Strong coding skills (Python, C++, or similar)with the ability to prototype, test, and deploy ML/CV models in productionenvironments.
  • Demonstrated ability to lead large-scaleengineering projects or device development from concept throughimplementation.
  • Hands-on experience with IIoT hardwaredesign, configuration, and integration for operational improvements.
  • Strong knowledge of system design, materialhandling, and human-machine interaction principles.
  • Exceptional program management,communication, and stakeholder management skills.

Nice-to-Have Qualifications
  • Advanced Python programming skills fordata modelling, simulation, and rapid prototyping.
  • Experience with system emulation andtesting environments.
  • Strong background in cross-functionalcollaboration within large, fast-paced, and dynamic operationalenvironments.
  • Familiarity with 3D modelling, CAD tools,or hardware prototyping.