Foundry Automation ML Engineer (AI)

TL;DR

Foundry Automation ML Engineer (AI): Building scalable ML pipelines and infrastructure for semiconductor factories with an accent on data processing, model training, inference, and MLOps. Focus on deploying models via Docker/Kubernetes, optimizing performance on CPUs/GPUs, and integrating with cloud-native platforms for production reliability.

Location: On-site presence required in Hillsboro, Oregon, US

Salary: $149,750–$275,580 USD

Company

hirify.global Foundry delivers state-of-the-art semiconductor manufacturing, process technology, and supply chain for AI-era products.

What you will do

• Design, build, and maintain scalable ML pipelines for data processing, training, and inference in on-prem cloud environments.
• Prepare large-scale datasets and develop APIs/microservices for ML application stacks.
• Monitor, debug, and optimize deployed models for performance, latency, and cost.
• Implement MLOps practices including model versioning, CI/CD, and containerization with Docker/Kubernetes.
• Collaborate with software developers, data scientists, and DevOps to integrate ML into products.
• Leverage hirify.global's cloud-native ML platforms to accelerate deployment lifecycles.

Requirements

• Bachelor's in Computer Science, Computer Engineering, Data Science, Computational Physics, or Applied AI with 5+ years experience OR Master's with 3+ years OR PhD with 6+ months.
• Programming in Python with unit testing; software engineering principles (data structures, algorithms, OOP).
• Experience with image analytics (OpenCV) and ML frameworks (PyTorch, Scikit-learn, TensorFlow).
• Strong knowledge of algorithm optimization for CPUs/GPUs, AI fundamentals, deep learning.
• MLOps, CI/CD, Kubernetes, ML pipelines; proven ML model development/deployment.
• Machine learning algorithms: supervised/unsupervised learning, deep learning, reinforcement learning, Bayesian analysis.

Nice to have

• 1+ years in semiconductor manufacturing/design problems.
• Deep learning or image analytics experience.
• Addressing complex use cases across domains; strong communication/problem-solving.
• Prototypes/demos; fine-tuning visual language models (Florence, QWEN).

Culture & Benefits

• Competitive pay, stock bonuses, health, retirement, and vacation benefits.
• Part of worldwide factory network focused on innovation and customer delight.
• Shift 1 (United States of America).