Lab and Data Automation Engineer

2 Months ago • All levels • Data Analysis • $143,100 PA - $264,200 PA

Job Summary

Job Description

In this role, you will develop methods to improve and automate the collection, storage, processing, and visualization of silicon validation data from labs worldwide. You’ll build and deploy scalable data pipelines using scheduling systems and design infrastructure to support distributed validation across bare metal macOS, Docker, and Kubernetes environments. You will also automate the setup of silicon validation environments and manage data migration across systems. A part of the role includes instrument tracking and network automation—integrating with lab hardware to configure devices, manage network environments, monitor instrument status, and collect validation data securely and at scale. For efficient and insightful data analytics, you’ll build AI/ML based tools that accelerate data analysis and integrate with existing data analysis platforms. This includes tracking power utilization of lab equipment, identifying patterns in usage, and optimizing for future demand through predictive modeling. This work involves close collaboration with hardware, software, and infrastructure teams to enable rapid data exploration, debug large-scale systems, and implement alerting mechanisms that enhance observability and transparency across automation workflows.

Job Details

In this role, you will develop methods to improve and automate the collection, storage, processing, and visualization of silicon validation data from labs worldwide. You’ll build and deploy scalable data pipelines using scheduling systems and design infrastructure to support distributed validation across bare metal macOS, Docker, and Kubernetes environments. You will also automate the setup of silicon validation environments and manage data migration across systems. A part of the role includes instrument tracking and network automation—integrating with lab hardware to configure devices, manage network environments, monitor instrument status, and collect validation data securely and at scale. For efficient and insightful data analytics, you’ll build AI/ML based tools that accelerate data analysis and integrate with existing data analysis platforms. This includes tracking power utilization of lab equipment, identifying patterns in usage, and optimizing for future demand through predictive modeling. This work involves close collaboration with hardware, software, and infrastructure teams to enable rapid data exploration, debug large-scale systems, and implement alerting mechanisms that enhance observability and transparency across automation workflows.

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