PDF Solutions, Inc.

Senior Software Applications Engineer (AI/ML)

PDF Solutions, Inc. • $130K — $180K *
Milpitas, CA 95035In-Person
Information Technology
Less than 5 years of experience
Reposted Today
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Job Overview by Ladders

Qualifications

  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, Materials Science, or related field.
  • Proficiency in Python and deep learning frameworks like TensorFlow and PyTorch, specifically for computer vision tasks.
  • Familiarity with semiconductor manufacturing processes or inspection metrology is preferred.
  • Experience handling large datasets with tools like Pandas, NumPy, and SQL for data management.
  • Strong analytical skills for translating complex manufacturing defects into actionable data models.

Responsibilities

  • Design and implement advanced ML/AI algorithms for defect classification in semiconductor inspection.
  • Analyze large defect datasets to uncover patterns and trends that inform model development.
  • Train, validate, and deploy defect classification models ensuring performance and accuracy.
  • Continuously enhance the defect classification system's accuracy, efficiency, and reliability through optimization.

Benefits

  • Opportunity to work on cutting-edge machine learning and AI solutions in a specialized industry.
  • Collaborative environment with cross-functional teams in hardware and software development.
  • Career growth potential in a rapidly evolving technology field.
Full Job Description
Overview

Role Summary

We are seeking a Senior Applications Engineer to join our team, focusing on the development of cutting-edge machine learning and artificial intelligence solutions for the semiconductor industry. The ideal candidate will have extensive experience in creating robust and scalable software, with a strong background in data analysis, machine learning, and containerization technologies.

Responsibilities

  • Design and Implement ML/AI Algorithms: Help develop and implement advanced machine learning and AI-based algorithms for the automatic classification of defects in semiconductor inspection tools.
  • Data Analysis: Analyze large volumes of defect data to identify critical patterns, trends, and anomalies, using this analysis to inform model development.
  • Training and Model Development: Train, validate, and deploy defect classification models, ensuring they meet strict performance and accuracy requirements.
  • System Optimization: Continuously improves the accuracy, efficiency, and reliability of the defect classification system through iterative development and optimization.


Qualifications

    • Education: Bachelor's or Master's degree in Computer Science, Electrical Engineering, Materials Science, or a related technical field.
    • Machine Learning Expertise: Proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch specifically for computer vision tasks (CNNs, Transformers).
    • Semiconductor Knowledge: Familiarity with semiconductor manufacturing processes or inspection metrology is highly preferred.
    • Data Proficiency: Experience handling large datasets and using tools like Pandas, NumPy and SQL for data preprocessing and feature engineering.
    • Problem Solving: Strong analytical mindset with the ability to translate complex manufacturing defects into actionable data models, data ingestion, analysis, and visualization.

Preferred Skills
    • Experience with Mismatched Data or Active Learning techniques to handle rare defect types.
    • Knowledge of ML Ops tools (ML Flow, zen Flow etc.) for model deployment and monitoring in a production environment.
    • Excellent communication skills to collaborate with cross-functional hardware and software teams.

Pay Range

USD $130,000.00 - USD $180,000.00 /Yr.

About PDF Solutions, Inc.

PDF Solutions, Inc. is a provider of infrastructure technologies and services for integrated circuits (IC). The Company's technologies and services focus on the IC manufacturing process life cycle. It operates in the segment of licensing and implementation of yield improvement solutions for integrated circuit manufacturers. Its solutions combine software, test chips, an electrical wafer test system, methodologies and professional services. The Company's characterization vehicle infrastructure (CVi) enables customers to electrically characterize the manufacturing process, and establish fail-rate information needed to calibrate manufacturing yield models and prioritize yield improvement activities. Its Exensio YieldAware solution incorporates all of the components of solutions, such as CVi, yield management software systems, and business intelligence dashboards. The Company's Exensio product family includes Exensio-Yield, Exensio-Control, Exensio-Test and Exensio-Char.
Learn more about PDF Solutions, Inc.
Size
407 employees
Market Cap
$1 billion
Industry
Manufacturing & Automotive
Net Income
-$40.3 million
5 Year Trend
+0.7%
Revenue
$88 million
NASDAQ
PDFS
* Ladders Estimates

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