Software Engineer, Machine Learning, GPU and TPU Accelerators

corporate_fareGoogleplaceSunnyvale, CA, USA

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 2 years of experience in software development (e.g., C++, Python), and with data structures/algorithms.
• 1 year of experience in compilers, accelerators, or equivalent performance improvements.

Preferred qualifications:

• Master's degree or PhD in Computer Science or a related technical field or equivalent practical experience.
• Experience with post-training quantization, quantized aware training, or quantized training for ML models.
• Experience with foundational models and Large Language Models.
• Understanding of the ML modeling techniques and trends.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.

Responsibilities

• Analyze and improve performance of Machine Learning (ML) models.
• Contribute to research and development of performance algorithms.
• Contribute to the creation of automated processes to advance the adoption of performance improvements in Google's Machine Learning (ML).
• Implement solutions in ML areas, utilize ML infrastructure, and contribute to model enhancement and data processing.
• Collaborate with peers and stakeholders through design and code reviews to ensure standard procedures amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).