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Machine Learning Operations Contractor

Fremont, CA, United States

Pay
Pay not listed
Work setting
On-site stated — work setting source
Working Conditions On-site 6-12 months temporary assignment
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Employment
Employment terms need review — employment source
We are seeking a Machine Learning Operations (MLOps) Contractor to drive semiconductor laser design and manufacturing excellence through the development and deployment of AI/ML within production. The emphasis will be on yield improvement, screening accuracy, and design optimization. The MLOps Contractor will develop and validate models based on extensive production data and deploy scalable models through a combination of cloud-based infrastructure and on-premises high performance inference. This position represents a unique opportunity to make an impactful contribution to the laser manufacturing industry and to pioneer AI/ML integration across Coherent international manufacturing sites. This is a contract-based position, ideal for a data scientist or engineer with strong AI/ML expertise and a background in photonics, semiconductor device physics, or semiconductor manufacturing. Primary Duties & Responsibilities
Employment type in the employer’s listing: Full time
From the employer’s posting
Apply at Coherent

What you’ll work on

Full posting
  • Enhance data pipelines across wafer processes, die-level test, and experimentation

  • Develop supervised and unsupervised models for yield prediction and performance screening

  • Deploy scalable models on cloud infrastructure and on-premises high performance inference

  • Integrate semiconductor laser physics into ML models for better interpretability

  • Document methodologies, model performance, and research findings clearly

From the employer’s posting
Enhance data pipelines across wafer processes, die-level test, and experimentation.
Develop supervised and unsupervised models for yield prediction and performance screening.
deploy scalable models through a combination of cloud-based infrastructure and on-premises high performance inference
Integrate domain knowledge from semiconductor laser physics into ML models for improved interpretability.
Document methodologies, model performance, and research findings clearly.

What you’ll bring

All qualifications

Core experience

  • Expertise with ML frameworks: TensorFlow, PyTorch, scikit-learn.
  • 6-12 months temporary assignment
  • Proficiency in both Python and C/C++ programming data structures for performance optimization
  • Experience in high-performance ML inference (LibTorch, CUDA, ONNX)
  • Experience with cloud-based ML platforms (AWS, GCP, Azure) and MLOps platforms such as Kubernetes
  • Ability to visualize and communicate insights effectively
Qualification wording
Expertise with ML frameworks: TensorFlow, PyTorch, scikit-learn.
6-12 months temporary assignment
Proficiency in both Python and C/C++ programming data structures for performance optimization
Experience in high-performance ML inference (LibTorch, CUDA, ONNX)
Experience with cloud-based ML platforms (AWS, GCP, Azure) and MLOps platforms such as Kubernetes
Ability to visualize and communicate insights effectively
Education & alternatives
Education & Experience - B.S. with 5-year industry experience or M.S./ Ph.D. with 2-year industry experience in Electrical Engineering, Computer Science, Physics, Photonics, or related field. - Proven track record in AI/ML deployment and integration within high visibility projects.

Tools in this posting

  • C
  • C++
  • Python
  • AWS
  • Azure
  • GCP
  • Kubernetes
  • PyTorch
  • scikit-learn
  • TensorFlow
Source — Tool mentions in context
- Expertise with ML frameworks: TensorFlow, PyTorch, scikit-learn. - Proficiency in both Python and C/C++ programming data structures for performance optimization - Experience in high-performance ML inference (LibTorch, CUDA, ONNX)
- Experience in high-performance ML inference (LibTorch, CUDA, ONNX) - Experience with cloud-based ML platforms (AWS, GCP, Azure) and MLOps platforms such as Kubernetes - Ability to visualize and communicate insights effectively
Skills - Expertise with ML frameworks: TensorFlow, PyTorch, scikit-learn. - Proficiency in both Python and C/C++ programming data structures for performance optimization

Posting record

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Open 4 monthsWe first saw this listing 139 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jun 4, 2026 · 139 days ago
Recorded sightings
327
Last seen by us
Oct 21, 2026

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Job description

View original posting ↗

We are seeking a Machine Learning Operations (MLOps) Contractor to drive semiconductor laser design and manufacturing excellence through the development and deployment of AI/ML within production. The emphasis will be on yield improvement, screening accuracy, and design optimization. The MLOps Contractor will develop and validate models based on extensive production data and deploy scalable models through a combination of cloud-based infrastructure and on-premises high performance inference. This position represents a unique opportunity to make an impactful contribution to the laser manufacturing industry and to pioneer AI/ML integration across Coherent international manufacturing sites. This is a contract-based position, ideal for a data scientist or engineer with strong AI/ML expertise and a background in photonics, semiconductor device physics, or semiconductor manufacturing.

 

Primary Duties & Responsibilities

Data Processing and Model Development

  • Enhance data pipelines across wafer processes, die-level test, and experimentation.
  • Develop supervised and unsupervised models for yield prediction and performance screening.
  • The ideal candidate will be proficient in data pre-processing, feature extraction, dimensionality reduction, clustering, classification, and regression. 
  • Experience with NN architectures such as CNNs, AEs, GANs and with ensemble learning methods including gradient boosting and random forests is preferred.

 Validation and Deployment 

  • Apply model selection to identify effective approaches and validate models using known techniques.
  • Integrate domain knowledge from semiconductor laser physics into ML models for improved interpretability. Familiarity with inverse design concepts is a plus.

Collaboration and Reporting

  • Work closely with photonics researchers and process engineers to align ML approaches with experimental and production objectives and quantify cost-benefit analysis.
  • Document methodologies, model performance, and research findings clearly.
  • Provide regular updates and deliverables to project stakeholders.

Education & Experience

  • B.S. with 5-year industry experience or M.S./ Ph.D. with 2-year industry experience in Electrical Engineering, Computer Science, Physics, Photonics, or related field.
  • Proven track record in AI/ML deployment and integration within high visibility projects. 

Skills

  • Expertise with ML frameworks: TensorFlow, PyTorch, scikit-learn.
  • Proficiency in both Python and C/C++ programming data structures for performance optimization
  • Experience in high-performance ML inference (LibTorch, CUDA, ONNX)
  • Experience with cloud-based ML platforms (AWS, GCP, Azure) and MLOps platforms such as Kubernetes
  • Ability to visualize and communicate insights effectively
  • Background in photonics, semiconductor devices, or manufacturing yield optimization is a strong plus

Working Conditions

  • On-site
  • 6-12 months temporary assignment

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 talentacquisition@coherent.com.


 

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Location & working pattern

Fremont, CA, United States

Working Conditions - On-site - 6-12 months temporary assignment
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