Machine Learning / Computer Vision

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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