Semiconductor Data Science and Machine Learning Engineer
Role details
Job location
Tech stack
Job description
The Semiconductor Data Science and Machine Learning Engineer will be part of a team to develop semiconductor-related automated vision systems and big data projects. This position will help to improve yield, improve process control, and increase opereational effiency. This position will develop and refine machine learning models, analyze complex datasets, and apply deep semiconductor process knowledge to enable smart manufaturing goals. The role will include collaborating with crossfunctional teams to build scalable data systems and analytical tools that enhance defect analysis, streamline data review, and strengthen feedback loops across HFTC., * Lead crossfunctional engagement with semiconductor fab process engineering and integration teams to align data insights, clarify process requirements, and ensure model yield framework outputs effectively support decisionmaking.
- Develop, train, and continuously refine machine learning models using optical inspection data to support yield determination, defect classification, and timely process feedback.
- Build scalable data pipelines, tooling, and analytical frameworks capable of supporting complex defect analysis and highvolume data processing.
- Apply deep semiconductor process knowledge to validate model assumptions, anticipate edge cases, and ensure meaningful interpretation of data in its physical process context.
- Communicate findings, process implications, and recommended actions clearly to stakeholders ranging from peers to leadership.
Requirements
- Bachelor's, Master's, or Ph.D. in Data Science, Electrical Engineering, Computer Science, Materials Science, Applied Physics, or related fields.
- 5+ years of experience developing and deploying machine learning models using ONNX for classification, pattern recognition, anomaly detection, or related tasks (MS with 2-3+ years/PhD with 1+ years of applicable experience).
- At least 3 years of experience in semiconductor manufacturing, processes or integration engineering.
- Ability to work with crossfunctional technical teams, interfacing with process and integration teams.
- Strong communication and collaboration skills are required.
Location: This role requires an in-person, hands-on engineer who can physically work with the test systems in Santa Rosa, CA.
This position requires access to certain goods, software, technology, or technical data subject to U.S. export control laws and regulations. Under these laws and regulations, U.S. persons (which includes U.S. citizens, U.S. nationals, lawful permanent residents, refugees, and asylees) working for Keysight can access export-controlled items without authorization from the U.S. government. For any individual who is not a U.S. person, Keysight may need authorization from the U.S. Department of State, U.S. Department of Commerce, or other appropriate federal agency before the individual can access export-controlled items. Employment in this position for non-U.S. persons is contingent on Keysight's ability to obtain any required government authorizations.Candidates must be a U.S. citizen or lawful permanent resident of the U.S., or protected individual, having authorization from the U.S. government for export-controlled items under 8 U.S.C. 1324b(a)(3).
Benefits & conditions
The level of role will be based on applicable experience, education and skills; Most offers will be between the minimum and the midpoint of the Salary Range listed below.
Santa Rosa, CA MIN $126,930 MID $169, 240- MAX $211,550
Note:For other locations, pay ranges will vary by region
This role is eligible for Keysight Results Bonus Program
US Employees may be eligible for the following benefits:
- Medical, dental and vision
- Health Savings Account
- Health Care and Dependent Care Flexible Spending Accounts
- Life, Accident, Disability insurance
- Business Travel Accident and Business Travel Health
- 401(k) Plan
- Flexible Time Off, Paid Holidays
- Paid Family Leave
- Discounts, Perks
- Tuition Reimbursement
- Adoption Assistance
- ESPP (Employee Stock Purchase Plan)