Primary 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.
Skills
The 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
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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.
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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 Conditions
The 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 Requirements
All employees are required to follow the site EHS procedures and Coherent Corp. Corporate EHS standards.
Quality and Environmental Responsibilities
Depending 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.
Culture Commitment
Ensure adherence to company’s values (ICARE) in all aspects of your position at Coherent Corp.:
Integrity – Create an Environment of Trust
Collaboration – Innovate Through the Sharing of Ideas
Accountability – Own the Process and the Outcome
Respect – Recognize the Value in Everyone
Enthusiasm – Find a Sense of Purpose in Work
Coherent Corp. is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.
If you need assistance or an accommodation due to a disability, you may contact us at [email protected].
Note to recruiters and employment agencies: We will not pay for unsolicited resumes from recruiters and employment agencies unless we have a signed agreement and have required assistance, in writing, for a specific opening.
Skills Required
- At least 5 years of experience with AI and preferably machine learning
- At least 3 years of experience in a production environment
- Bachelor's degree in Electrical Engineering, Computer Science, Physics, or a related field with specialization in Data Science, AI/ML, or Statistics
- Expertise in deep learning frameworks such as PyTorch and TensorFlow
- Expertise in deep learning architectures including CNNs, RNNs, and GANs
- Expertise in machine learning methods including Random Forests and Gradient Boosting
- Experience with clustering, feature engineering, and dimensionality reduction
- Proficiency deploying ML models 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
- Ability to take analyses from problem definition through deployment, validation, and communication of results
- Programming skills in Python and experience with common data-science and machine-learning libraries
- Familiarity with CUDA, LibTorch, ONNX Runtime, C++, and data structures
- Experience with cloud-based ML training and inference using AWS, GCP, Azure, or Databricks
- Familiarity with machine vision, defect detection, or OCR
- Familiarity with Hadoop and Spark
- Exposure to manufacturing, wafer fabrication, photonics, or telecommunications
- Master's degree
Coherent Corp. Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Coherent Corp. and has not been reviewed or approved by Coherent Corp..
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Healthcare Strength — Healthcare Strength: Health coverage includes multiple national and region-specific options (UHC HDHP/HSA, PPO, EPO; Kaiser in CA; Health Net in OR) plus separate dental (Delta Dental) and vision (VSP), indicating strong breadth and choice. This breadth supports a solid total package in certain roles and locations.
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Equity Value & Accessibility — Equity Value & Accessibility: An Employee Stock Purchase Plan allows buying shares at 85% of market price with contributions up to 10% of pay, expanding ownership access. This feature can materially bolster total rewards even when base pay is mid‑pack.
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Leave & Time Off Breadth — Leave & Time Off Breadth: Paid time off includes 15 vacation days for new hires, 10 paid holidays, and additional paid time during a December shutdown. This structure provides a clear and competitive baseline for time away from work.
Coherent Corp. Insights
What We Do
Coherent empowers market innovators to define the future through breakthrough technologies, from materials to systems. We deliver innovations that resonate with our customers in diversified applications for the industrial, communications, electronics, and instrumentation markets. Headquartered in Saxonburg, Pennsylvania, Coherent has research and development, manufacturing, sales, service, and distribution facilities worldwide. For more information, please visit us at coherent.com.






