Advantest Cloud Solutions (ACS) is looking to accelerate the integration of AI into semiconductor test and measurement systems by building intelligent, scalable, and secure platforms where AI agents collaborate with customers in real-world workflows.
Requirements
- Strong coding skills in Python (experience with C++/Java a plus).
- Experience with one or more machine learning frameworks (PyTorch, TensorFlow, Scikit-learn).
- Familiarity with SQL/NoSQL databases and data processing workflows, including experience working with Parquet, JSON, or other data lake platforms.
- Practical experience with containers (Docker) and preferably Kubernetes.
- Understanding of software engineering best practices (CI/CD, testing, version control).
- Experience working in the semiconductor industry, especially with ATE platforms and workflows.
- Familiarity with message queuing systems (Kafka, RabbitMQ).
Responsibilities
- Build and deploy AI solutions for real-world use cases such as predictive analytics, anomaly detection, generative AI, and workflow automation.
- Develop end-to-end AI pipelines including data ingestion, preprocessing, model training, validation, deployment, and monitoring.
- Work with ML frameworks (PyTorch, TensorFlow, Scikit-Learn, XGBoost) and integrate models into applications and services.
- Collaborate with software and infrastructure teams to ensure AI services run efficiently in containerized environments (Docker, Kubernetes).
- Experiment with LLMs, multi-agent systems, and prompt engineering, focusing on practical integration into production.
- Participate in team discussions, design reviews, and troubleshooting sessions to continuously improve system reliability.
- Contribute to a culture of collaboration, learning, and problem-solving across global ACS teams.
Other
- Bachelor's degree in Computer Science, Engineering, or related field (or equivalent practical experience).
- 2-3+ years of hands-on software development or ML engineering experience.
- Strong team player with good communication skills and a problem-solving mindset.
- A can-do attitude — comfortable learning new tools, debugging issues, and delivering solutions under time constraints.
- Prior contributions to AI/ML projects in production environments.
