Staff Software Engineer, Platform-Aware AutoML

Minimum qualifications: Bachelor’s degree or equivalent practical experience. 8 years of experience in software development, and with data structures or algorithms. 5 years of experience in testing, and launching software products, and 3 years of experience with software design and architecture. 5 years of experience leading Machine Learning design and optimizing Machine Learning infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning, etc.). Experience developing software applications using Python. Preferred qualifications: Master’s degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience. 3 years of experience in a technical leadership role and setting technical direction. 3 years of experience in working cross-functionally, or cross-business projects. Experience with Machine Learning (ML) based performance work. Experience in spanning across various Machine Learning (ML) domains (e.g., Deep Learning, Reinforcement Learning, Neural Networks, Autoregressive Models, etc.). Knowledge of computer architecture and performance analysis. 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. In this role, you will be responsible for performance and extracting maximum for AI/ML training workloads. You will drive Machine Learning (ML) performance by identifying performance opportunities in Google production and research Machine Learning workloads, landing optimizations.

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