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

Bachelor's degree in Computer Science, Electrical Engineering, Robotics, or related field • Experience: 4-6 years of industry experience in computer vision engineering OR Master's degree with 2-4 ...

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Computer Vision Engineer information

See Seattle, WA salary details

$55.2K

$138.4K

$156.6K

How much do computer vision engineer jobs pay per year?

As of May 30, 2026, the average yearly pay for computer vision engineer in Seattle, WA is $138,366.00, according to ZipRecruiter salary data. Most workers in this role earn between $127,000.00 and $149,700.00 per year, depending on experience, location, and employer.

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 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 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.

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 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 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:
Infographic showing various Computer Vision Engineer job openings in Seattle, WA as of May 2026, with employment types broken down into 2% Internship, 96% Full Time, and 2% Contract. Highlights an 85% In-person, 4% Hybrid, and 11% Remote job distribution, with an average salary of $138,366 per year, or $66.5 per hour.
Engineering Manager II, Computer Vision - Applied AI

Engineering Manager II, Computer Vision - Applied AI

Uber

Seattle, WA • On-site, Remote

Other

Retirement

Posted 12 days ago


Uber rating

7.2

Company rating: 7.2 out of 10

Based on 100 frontline employees who took The Breakroom Quiz

3rd of 9 rated taxi private hire


Job description

**About the Role**Applied AI at Uber builds intelligent systems that power critical product experiences across the platform. As an Engineering Manager II - Computer Vision, you will lead a high-performing team of engineers developing state-of-the-art vision and multimodal systems that support large-scale, production-grade applications such as document intelligence, onboarding automation, transcription systems, and other visual AI workflows.You will be responsible for driving technical execution and long-term strategy across computer vision initiatives, partnering closely with Product, ML Infrastructure, and cross-functional stakeholders. This role requires strong technical depth in machine learning systems and distributed production environments, combined with exceptional people leadership and organizational impact.You will shape multi-year technical direction, elevate engineering standards, and ensure your team delivers reliable, scalable, and high-quality AI solutions that drive measurable business impact.**What You Will Do:**- Lead and manage a team of software and deep learning engineers, delivering high-quality computer vision products and scalable ML systems.- Develop and execute technical strategies that align with business objectives, translating complex product requirements into clear, multi-quarter roadmaps and platform architecture.- Collaborate cross-functionally with Product, ML Infra, Data, and partner engineering teams to drive technical innovation and deliver measurable impact across business units.- Plan, prioritize, and oversee execution, ensuring timely delivery through effective delegation, empowering tech leads, and maintaining high engineering standards.- Mentor, grow, and develop a world-class team of deep learning engineers, fostering a culture of continuous learning, operational excellence, and high performance.**Basic Qualifications:**- Bachelor's degree in Computer Science, Engineering, or equivalent technical background with exceptional demonstrated impact.- 12+ years of industry experience, including 3+ years leading high-performing engineering teams in large-scale distributed production environments.- Proven track record of delivering sustained business impact over multiple quarters through strong execution and organizational leadership.- Experience driving timely execution through effective delegation, empowering technical leads, and leading cross-team alignment by setting clear priorities and resolving trade-offs.- Demonstrated ability to translate complex business problems into multi-year technical strategies and cross-team platform architectures.**Preferred Qualifications:**- Strong experience training and optimizing large-scale vision or multimodal models, including Vision-Language Models (VLMs) or foundation models.- Deep understanding of computer vision techniques such as object detection, segmentation, OCR, document layout understanding, and point cloud processing.- Experience working with large-scale distributed systems and real-time data processing environments.- 3+ years of experience managing a team of senior engineers, with demonstrated strength in coaching, career development, and building inclusive, high-performing teams.- Experience partnering closely with ML Infrastructure teams to scale training, evaluation, and deployment pipelines.For San Francisco, CA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year.For Seattle, WA-based roles: The base salary range for this role is USD$232,000 per year - USD$258,000 per year.For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp

All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link [https://jobs.uber.com/en/benefits](https://jobs.uber.com/en/benefits).Uber's mission is to reimagine the way the world moves for the better

Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law

We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](https://forms.gle/aDWTk9k6xtMU25Y5A).Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office

For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.


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