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Computer Vision Engineer Jobs in Hillsboro, OR (NOW HIRING)

Lam Research

Vision Systems Engineer 4

Tualatin, OR · On-site

What you'll do Design, develop, and deploy computer vision algorithms for detection, classification ... Mentor junior engineers and provide technical guidance on best practices in data science and ...

Hp

AI Solution Engineer

Vancouver, WA · On-site

$130K - $205K/yr

AI Solution Engineer Description - We are seeking an innovative and results-driven AI Solution ... Computer Vision, and Edge AI to create intelligent solutions for enterprise customers. As a key ...

Fresh Consulting

Sr. DevOps Engineer

Portland, OR · On-site

$75 - $85/hr

Position Overview We're seeking an experienced senior development operations (DevOps) engineer to own the build, test, and deployment pipeline for our distributed computer vision platform running at ...

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All JobsComputer Vision Engineer JobsComputer Vision Engineer Jobs in Hillsboro, OR

Computer Vision Engineer information

See Hillsboro, OR salary details

$52.8K

$132.3K

$149.7K

How much do computer vision engineer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for computer vision engineer in Hillsboro, OR is $132,340.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,400.00 and $143,200.00 per year, depending on experience, location, and employer.

What is a computer vision engineer?

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 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 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.

More about Computer Vision Engineer jobs

What cities near Hillsboro, OR are hiring for Computer Vision Engineer jobs?

Cities near Hillsboro, OR with the most Computer Vision Engineer job openings:

Computer Vision Engineer jobs near you
Infographic showing various Computer Vision Engineer job openings in Hillsboro, OR as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 16% Part Time, and 6% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $132,340 per year, or $63.6 per hour.

Machine Learning / Computer Vision

Hillsboro, OR • On-site

Chabez Tech LLC
See more jobs at Chabez Tech LLCexternal

Other

Posted 5 days ago

Job description

Role: Machine Learning / Computer Vision

Location: Hillsboro OR - Onsite

Duration: 2 years Contract

 

We develop AI-powered semiconductor wafer inspection systems using computer vision and machine learning to analyze images at the limits of physical measurement.

 

Key Responsibilities

  • Build and train Computer Vision models for image classification, especially with imbalanced or poor-quality images.
  • Develop image embeddings, metric learning, and similarity/retrieval systems.
  • Build Few-Shot Learning / Cold-Start models using limited training data.
  • Implement model confidence, uncertainty, calibration, and anomaly/novelty detection so models avoid incorrect predictions.
  • Optimize ML models for fast and efficient inference, including GPU/edge environments.
  • Build and manage MLOps pipelines including model monitoring, drift detection, automated retraining, testing, and deployment.
  • Work closely with domain/subject-matter experts to understand real-world data and improve model performance.

Must-Have Skills

  • 5+ years of hands-on ML/Computer Vision experience.
  • Strong Python programming.
  • Strong experience with PyTorch or similar deep-learning frameworks.
  • Knowledge of modern Computer Vision architectures: CNNs, Vision Transformers (ViT).
  • Strong experience in at least 2 of the following:
    • Image Classification / Detection
    • Metric Learning / Embeddings / Similarity Search
    • Few-Shot / Self-Supervised Learning
    • Model Calibration / Uncertainty / Novelty Detection
    • MLOps / Model Lifecycle
  • Strong understanding of model validation, experimentation, and data quality.

Experience working with large, messy, or domain-specific datasets.

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