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In this role, you will help to develop and maintain emulation infrastructure, tools, and workflow methodologies supporting our Application-Specific Integrated Circuit (ASIC) projects. You will provide emulation infrastructure and methodologies for supporting these projects. You will work with other emulation team members as well as designers, verification engineers, and software teams. You will work with our external vendors, lab support teams, networking and security, and Electronic Design Automation (EDA) tooling and methodology teams to deliver emulation-based prototyping capabilities for our ASIC projects. You will also assist in compiling projects specifying our prototyping platforms, debugging issues in both infrastructure and design, supporting the hardware and lab bring up, and verifying our ASIC systems.

The AI and Infrastructure team is redefining whats possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.

We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.

Responsibilities
Help in maintaining and upgrading emulation infrastructure and act as a primary interface to emulation vendors.
Explore emulation methodologies, gather feedback from the team, and implement emulation workflows and methodologies.
Create tooling and automation to support emulation EDA tools, licensing, and job management in Google infrastructure.
Support emulation team members with debugging hardware, tooling, and project-specific issues.
Help to bring up external interfaces (e.g., USB, PCIe, Ethernet, etc.) on the emulation platforms and create standalone test cases for tool issues encountered in the emulation compile and runtime flows.

In this role, you will leverage your expertise in distributed systems, data engineering, and software development to design, build, and deploy high-performance solutions. You will take a leading role in developing and maintaining a cutting-edge online machine learning system powered by PyTorch/Tensorflow models and Triton inference server.

This is an opportunity to work on complex, large-scale systems that serve billions of requests, shaping the future of ad tech and ML-driven optimization.

What you'll be doing
Architect and Build: Design, develop, and deploy robust, scalable, and high-performance distributed systems that form the backbone of ironSource's next-generation ML ad network.
Real-Time Ad Serving: Engineer and optimize critical systems for real-time ad serving, enabling machine learning models to make intelligent, low-latency decisions for optimal ad selection.
ML Infrastructure Innovation: Drive the evolution of our ML capabilities by researching, evaluating, and implementing cutting-edge techniques for feature stores, data aggregation, and model serving infrastructure.
Data Pipeline Engineering: Collaborate closely with data scientists and product managers to design, build, and maintain efficient and reliable data lakes and data pipelines, ensuring high-quality data for ML training and analytics.
Operational Excellence: Take ownership of key system components, ensuring their reliability, performance, and scalability in a production environment through proactive monitoring and continuous improvement.