Role OverviewThe Principal Machine Learning Engineer will develop and validate models for yield improvement, screening accuracy, and process optimization through application of model selection and hyperparameter tuning. They will collaborate with Photonics designers and process, reliability, and manufacturing engineers to align ML approaches with product objectives and to quantify cost-benefit analysis.
What You Will Do
The candidate will develop reusable data pipelines, analytical tools, dashboards, and model-monitoring methods. They will deploy AI/ML within manufacturing systems through a combination of Edge AI, API serving, Containerization, and Cloud-based training and inference. They will also support design of experiments, process characterization, and continuous improvement activities.
Why It Might Be a Fit
The candidate will have the opportunity to establish best practices for ML and share them across the site and other sites. They will also have the chance to work with a global leader in lasers, engineered materials, and networking components, with a comprehensive career development platform and a competitive compensation program.
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
Benefits
- Competitive compensation program
- Comprehensive career development platform
- Stability, longevity, and growth opportunities
]]>