Job DescriptionPrimary Duties & 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.
SkillsThe Candidate will have competency in the following areas:
- 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.
Education & Experience- The Candidate will have 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.
Working ConditionsThe job is on-site for the first three months, with the possibility to convert to hybrid afterwards. The job requires weekly morning hours and occasional evening and weekend hours. Travel to other Coherent sites in the Bay Area and the US may be possible to share knowledge with other experts.
Physical Requirements- Sitting or standing for several hours per day, with the option of having a sit-stand desk.
- Extensive keyboard and mouse work.
Safety RequirementsAll employees are required to follow the site EHS procedures and Coherent Corp. Corporate EHS standards.
Quality and Environmental ResponsibilitiesDepending on location, this position may be responsible for the execution and maintenance of the ISO 9000, 9001, 14001 and/or other applicable standards that may apply to the relevant roles and responsibilities within the Quality Management System and Environmental Management System.
