Machine Learning Operations Contractor

Coherent Corp. • Fremont, CA

136d • Onsite

About The Position

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.

Requirements

• 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.
• 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

Nice To Haves

• Experience with NN architectures such as CNNs, AEs, GANs and with ensemble learning methods including gradient boosting and random forests is preferred.
• Familiarity with inverse design concepts is a plus.
• Background in photonics, semiconductor devices, or manufacturing yield optimization is a strong plus

Responsibilities

• Enhance data pipelines across wafer processes, die-level test, and experimentation.
• Develop supervised and unsupervised models for yield prediction and performance screening.
• 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.
• 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.

What This Job Offers

• Career Level: Mid Level
• Number of Employees: 1,001-5,000 employees