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Computer Vision Engineer Jobs in Seattle, WA (NOW HIRING)

SID Global Solutions

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 ...

SID Global Solutions

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 ...

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All JobsComputer Vision Engineer JobsComputer Vision Engineer Jobs in Seattle, WA

Computer Vision Engineer information

See Seattle, WA salary details

$55.2K

$138.3K

$156.5K

How much do computer vision engineer jobs pay per year?

As of Jun 21, 2026, the average yearly pay for computer vision engineer in Seattle, WA is $138,288.00, according to ZipRecruiter salary data. Most workers in this role earn between $126,900.00 and $149,600.00 per year, depending on experience, location, and employer.

What are Computer Vision Engineers?

Computer Vision Engineers are professionals who develop algorithms and systems that enable computers to interpret and process visual information from the world, such as images and videos. They work on tasks like object detection, facial recognition, image segmentation, and more, often using machine learning and deep learning techniques. These engineers apply their expertise in fields like robotics, autonomous vehicles, healthcare, and augmented reality, turning raw visual data into actionable insights.

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

AspectComputer Vision EngineerMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, Electrical Engineering, or related; knowledge of image processing and computer vision librariesBachelor's or Master's in CS, Data Science, or related; strong programming and statistical skills
Work EnvironmentDevelops algorithms for image/video analysis, object detection, and recognition in tech, automotive, or healthcare industriesBuilds models for various data types, including text, images, and structured data across multiple sectors
Employer & Industry UsageTech companies, autonomous vehicles, robotics, healthcareTech firms, finance, e-commerce, healthcare, and research institutions

While both roles involve machine learning techniques, Computer Vision Engineers specialize in developing algorithms for visual data, whereas Machine Learning Engineers work on broader data modeling across various data types. The roles often overlap but differ mainly in focus and application areas.

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 strong background in computer science, mathematics, and machine learning, often supported by a relevant degree and experience with image processing algorithms. Familiarity with tools and frameworks such as OpenCV, TensorFlow, PyTorch, and proficiency in programming languages like Python or C++ is essential, along with knowledge of deep learning techniques. Analytical thinking, creativity, and effective communication are standout soft skills for this role. These skills and qualities are crucial for developing innovative vision solutions, interpreting complex data, and collaborating efficiently within interdisciplinary teams.

What Does a Computer Vision Engineer Do?

Computer vision is a branch of artificial intelligence that attempts to replicate human analytical processes by using algorithms and computer models to understand and identify patterns in images. As a computer vision engineer, you use software to handle the processing and analysis of large data populations, and your efforts support the automation of predictive decision-making efforts. Your responsibilities involve research, programming, data analysis, and user interface design. You may work on a variety of exciting development projects like self-driving cars, mobile devices, innovative features and capabilities in sports and entertainment, and the next generation of social media enhancements.

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

Computer Vision Engineers often encounter challenges such as ensuring model accuracy in diverse real-world conditions, optimizing models for efficiency on edge devices, and handling large-scale data processing. Deploying models to production requires balancing performance with resource constraints and addressing issues like latency, scalability, and data privacy. Collaborating closely with software engineers and data scientists is crucial to integrate solutions effectively and continuously monitor and improve model performance in live applications.
More about Computer Vision Engineer jobs
What are the most commonly searched types of Computer Vision Engineer jobs in Seattle, WA? The most popular types of Computer Vision Engineer jobs in Seattle, WA are:
What are popular job titles related to Computer Vision Engineer jobs in Seattle, WA? For Computer Vision Engineer jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Computer Vision Engineer jobs in Seattle, WA look for? The top searched job categories for Computer Vision Engineer jobs in Seattle, WA are:
What cities near Seattle, WA are hiring for Computer Vision Engineer jobs? Cities near Seattle, WA with the most Computer Vision Engineer job openings:
Computer Vision Engineer jobs near you
Computer Vision Engineer

Computer Vision Engineer

SID Global Solutions

Bellevue, WA

$125K - $148K/yr

Full-time

Posted 15 days ago

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 of complex cross-functional projects spanning organizations and geographies, ensuring delivery of impactful business outcomes. Engineering Solutions: Design and develop engineering solutions for material handling challenges, considering human-equipment interactions and operational excellence. IIoT Development: Develop, configure, and implement IIoT hardware to enhance equipment, processes, and operator workflows.

Simulation & Modeling: Collaborate with Scientists to create advanced simulation models and perform "what-if" scenario testing to drive optimal hardware and process solutions. Concept & Design Leadership: Lead concept efforts for optimal solutions including equipment specifications, material flow, ergonomics, associate experience, operational considerations, and site layout. Vendor & Stakeholder Collaboration: Partner with suppliers, vendors, and internal teams to deliver innovative solutions with scalability and efficiency.

Documentation & Standards: Ensure all solutions are documented with SOPs and/or structured change control, setting standards for engineering excellence. Multi-Project Management: Manage multiple initiatives simultaneously while influencing, negotiating, and communicating effectively with internal and external stakeholders. Thought Leadership: Deliver artifacts (research, schematics, prototypes, 3D models, analysis, test plans, narratives) that set benchmarks for organizational engineering standards.

Consensus Building: Communicate complex ideas clearly, harmonize diverse 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 production environments.

Demonstrated ability to lead large-scale engineering projects or device development from concept through implementation. Hands-on experience with IIoT hardware design, configuration, and integration for operational improvements. Strong knowledge of system design, material handling, and human-machine interaction principles.

Exceptional program management, communication, and stakeholder management skills. Nice-to-Have Qualifications Advanced Python programming skills for data modelling, simulation, and rapid prototyping. Experience with system emulation and testing environments.

Strong background in cross-functional collaboration within large, fast-paced, and dynamic operational environments. Familiarity with 3D modelling, CAD tools, or hardware prototyping.

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