Machine Learning Operations Engineer (MLOps)Frey Consulting Group • Fremont, California, United States
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Machine Learning Operations Engineer (MLOps)
Frey Consulting Group
- Fremont, California, United States
- Fremont, California, United States
About
Employment Type: Contract (40 hours per week)
Compensation: $50–$100 per hour
Benefits: Contractor position; conversion to full-time may be possible based on project success and business needs
Position Summary A global leader in photonics and semiconductor technology is seeking a Machine Learning Operations (MLOps) Engineer to help develop, deploy, and scale AI/ML solutions within advanced manufacturing operations. This is a highly visible, cross‑functional role focused on applying machine learning and artificial intelligence to improve manufacturing yield, process control, defect detection, and operational efficiency. The successful candidate will work directly with Process Engineering, Product Engineering, Test Engineering, Manufacturing, MES, and IT teams to build data pipelines, develop machine learning models, and deploy production‑ready AI solutions into manufacturing workflows. This role offers a rare opportunity to pioneer AI/ML capabilities within a cutting‑edge semiconductor and photonics manufacturing environment while directly impacting yield improvement and cost reduction initiatives.
What You'll Do
Partner with Process, Product, and Test Engineering teams to understand manufacturing workflows, data sources, and business objectives
Develop, train, validate, and optimize machine learning models for manufacturing applications
Build and maintain reliable data pipelines supporting model development and deployment
Apply supervised and unsupervised learning techniques to improve process control, yield, and defect detection
Define, monitor, and report KPIs related to model performance and manufacturing outcomes
Deploy machine learning models into production environments using APIs, containers, and orchestration platforms
Integrate AI/ML solutions with existing manufacturing systems, databases, MES platforms, and on‑premise infrastructure
Collaborate with Operations and Engineering stakeholders to identify new AI/ML opportunities
Monitor model performance, retrain models as necessary, and drive continuous improvement initiatives
Document methodologies, validation approaches, performance results, and improvement plans
Support knowledge transfer and collaboration with partner manufacturing sites deploying similar AI/ML solutions
What You Bring
Bachelor's degree in Computer Science, Electrical Engineering, Physics, Mathematics, Statistics, Data Science, Machine Learning, or related field required
5+ years of relevant experience, or Master's degree with 2+ years of experience
Strong expertise with at least one deep learning framework such as PyTorch, TensorFlow, or Keras
Experience with deep learning architectures such as CNNs, RNNs, VAEs, GANs, or related models
Experience with tree‑based learning methods including Random Forests, Gradient Boosting, or similar approaches
Strong understanding of data preprocessing techniques including normalization, denoising, feature engineering, and missing data handling
Experience with model development best practices including hyperparameter tuning, overfitting prevention, model validation, and k‑fold cross‑validation
Experience deploying machine learning models using REST APIs, containerization, and orchestration technologies
Strong Python programming and data analysis skills
Ability to work effectively across engineering, manufacturing, and operations teams
Proven track record of developing and deploying production‑ready AI/ML solutions
Preferred Qualifications
Experience with CUDA, ONNX, LibTorch, C++, and high-performance inference environments
Experience with machine vision, computer vision, OCR, defect detection, or image analytics
Knowledge of clustering, dimensionality reduction, and feature extraction techniques
Familiarity with AWS, Azure, GCP, or cloud-based AI/ML environments
Semiconductor manufacturing experience
Experience supporting manufacturing, quality, yield improvement, or industrial AI applications
Experience working with large manufacturing datasets and operational analytics
What You Get
Opportunity to build one of the first dedicated AI/ML programs within a major semiconductor manufacturing operation
Direct impact on yield improvement, manufacturing efficiency, and product quality
Exposure to cutting‑edge photonics and optical networking technologies supporting AI infrastructure growth
Highly visible role with significant cross‑functional collaboration
Opportunity to influence manufacturing operations on a global scale
Strong technical autonomy and ownership
Potential pathway into a long‑term AI/ML leadership role based on performance and business growth
Collaborative environment with experienced engineering, manufacturing, and product development teams
Opportunity to apply advanced machine learning techniques to real-world industrial challenges
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Languages
- English
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