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Lead Computer Vision Engineer Jobs in Beaverton, OR

Lam Research

Vision Systems Engineer 4

Tualatin, OR

Who we're looking for We are seeking a highly skilled Vision System Data Science Engineer to lead the design, development, and deployment of advanced computer vision and machine learning solutions ...

Hp

AI Solution Engineer

Vancouver, WA

$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 ...

Rapta, Inc

Senior Solutions Engineer, West Coast

Portland, OR · On-site

$58.50 - $75.50/hr

Backed by top investors and growing rapidly, we're a Portland-based team building computer vision ... Lead on-site training and solutions identification for Rapta vision robotic inspection cells.

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All JobsLead Computer Vision Engineer JobsLead Computer Vision Engineer Jobs in Beaverton, OR

Lead Computer Vision Engineer information

See Beaverton, OR salary details

$44.2K

$128.8K

$187.8K

How much do lead computer vision engineer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for lead computer vision engineer in Beaverton, OR is $128,793.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,600.00 and $140,500.00 per year, depending on experience, location, and employer.

What does a Lead Computer Vision Engineer do?

A Lead Computer Vision Engineer is responsible for overseeing the development and implementation of computer vision algorithms and systems. They guide a team of engineers, set technical direction, and ensure the successful deployment of image and video analysis solutions. Their work often involves tasks such as object detection, pattern recognition, and machine learning, as well as collaborating with other departments to integrate vision technologies into products. Additionally, they stay updated with the latest advancements in the field to maintain competitive and innovative solutions.

What are the key skills and qualifications needed to thrive as a Lead Computer Vision Engineer?

To thrive as a Lead Computer Vision Engineer, you need deep expertise in computer vision algorithms, machine learning, and programming languages such as Python or C++, usually backed by an advanced degree in computer science or a related field. Experience with tools like TensorFlow, PyTorch, OpenCV, and cloud-based deployment platforms, along with relevant certifications, is typically required. Strong leadership, project management, and communication skills help you guide teams and articulate technical solutions to stakeholders. These combined skills ensure the successful development and implementation of innovative vision systems that meet organizational goals.

How does a Lead Computer Vision Engineer typically collaborate with cross-functional teams during a project?

As a Lead Computer Vision Engineer, you will regularly work alongside product managers, data scientists, software engineers, and UX designers to ensure that computer vision solutions align with business objectives and user needs. This collaboration often involves translating technical requirements into practical deliverables, providing expertise during project planning, and integrating computer vision algorithms into production systems. Effective communication is crucial, as you may also be responsible for mentoring junior engineers and presenting progress to stakeholders. The role requires balancing hands-on development with leadership and coordination across disciplines.

What is the difference between Lead Computer Vision Engineer vs Computer Vision Engineer?

AspectLead Computer Vision EngineerComputer Vision Engineer
Required CredentialsBachelor's/Master's/PhD in CS, AI, or related fields; experience in leadership rolesBachelor's/Master's in CS, AI, or related fields; focus on technical skills
Work EnvironmentLeading projects, mentoring teams, strategic planningDeveloping algorithms, implementing models, testing
Employer & Industry UsageTech companies, autonomous vehicles, robotics, healthcareResearch labs, startups, tech firms, automotive

The main difference is that a Lead Computer Vision Engineer oversees projects and teams, focusing on strategy and leadership, while a Computer Vision Engineer primarily develops and implements algorithms. Both roles require strong technical skills, but the lead position involves more management responsibilities.

Infographic showing various Lead Computer Vision Engineer job openings in Beaverton, OR as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 18% Part Time, and 4% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $128,793 per year, or $61.9 per hour.

Machine Learning / Computer Vision

Hillsboro, OR • On-site

Chabez Tech LLC
See more jobs at Chabez Tech LLCexternal

Other

Posted 6 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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