Principal Machine Learning Engineer – Wafer Fabrication

Coherent • Fremont, CA

2d • Hybrid

About The Position

Develop and validate models for yield improvement, screening accuracy, and process optimization through application of model selection and hyperparameter tuning. Collaborate with Photonics designers and process, reliability and manufacturing engineers to align ML approaches with product objectives and to quantify cost-benefit analysis. Deploy AI/ML within manufacturing systems through a combination of Edge AI, API serving, Containerization, and Cloud-based training and inference. Partner with industrial and MES software engineers to integrate AI/ML pipelines within existing production workflows. Develop reusable data pipelines, analytical tools, dashboards, and model-monitoring methods. Support design of experiments, process characterization, and continuous improvement activities. Help establish best practices for ML, and share the practices across the site and other sites.

Requirements

• Expertise in deep learning frameworks such as Pytorch, TensorFlow
• Expertise deep learning architectures such as CNNs, RNNs, GANs
• Expertise in ML methods such as Random Forests and Gradient Boosting
• Experience with clustering, feature engineering, and dimensionality reduction methods
• Proficiency in ML model deployment through RESTful APIs, containerization, and container orchestration
• Experience with SQL and modern data-processing or data-platform technologies.
• Familiarity with statistical methods, experimental design, regression, classification, clustering, anomaly detection, and model evaluation
• Programming skills in Python and experience with common data-science and machine-learning libraries is a plus
• Familiarity with high-performance ML inference (CUDA, Libtorch, ONNX Runtime, C++ programming and data structures) is a strong plus
• Experience with cloud-based ML training and inference using AWS, GCP, Azure, or Databrix is a plus
• Familiarity with machine vision such as defect detection and OCR is a plus
• Familiarity with big data frameworks such as Hadoop and Spark is a plus
• Exposure to manufacturing, wafer fabrication, photonics , telecommunications is a plus
• Demonstrated ability to take an analysis from problem definition through deployment, validation, and communication of results.
• Minimum 5 years of experience with AI, preferably including ML, preferably with experience in statistical analytic techniques, and 3 years experience in a production environment.
• A Bachelor’s degree in Electrical Engineering , Computer Science, Physics, or related field with specialization in Data Science, AI/ML, or Statistics ; a Master’s degree is preferred.

Nice To Haves

• Familiarity with high-performance ML inference (CUDA, Libtorch, ONNX Runtime, C++ programming and data structures)
• Experience with cloud-based ML training and inference using AWS, GCP, Azure, or Databrix
• Familiarity with machine vision such as defect detection and OCR
• Familiarity with big data frameworks such as Hadoop and Spark
• Exposure to manufacturing, wafer fabrication, photonics , telecommunications
• A Master’s degree

Responsibilities

• Develop and validate models for yield improvement, screening accuracy, and process optimization through application of model selection and hyperparameter tuning.
• Collaborate with Photonics designers and process, reliability and manufacturing engineers to align ML approaches with product objectives and to quantify cost-benefit analysis.
• Deploy AI/ML within manufacturing systems through a combination of Edge AI, API serving, Containerization, and Cloud-based training and inference.
• Partner with industrial and MES software engineers to integrate AI/ML pipelines within existing production workflows.
• Develop reusable data pipelines, analytical tools, dashboards, and model-monitoring methods.
• Support design of experiments, process characterization, and continuous improvement activities.
• Help establish best practices for ML, and share the practices across the site and other sites.

Benefits

• Possibility to convert to hybrid after three months
• Travel to other Coherent sites in the Bay Area and the US may be possible to share knowledge with other experts.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal