Staff Software Engineer, Machine Learning Experimentation
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development and with data structures/algorithms in either (C++ OR Python).
- 5 years of experience with Machine Learning (ML) design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- Experience in a technical leadership role leading project teams and setting technical direction.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- Experience with large-scale distributed systems and scheduling infrastructure (e.g., Slurm, Borg, Xborg, Flume).
- Experience with build systems and infrastructure (e.g., Blaze, Bazel, etc.).
- Experience in measuring and improving system performance (e.g., profiling, system optimization).
- Experience with building developer tools.
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.
Our team builds and engineers infrastructure solutions that enable rapid ML research and development across Alphabet, with a focus on building tools that support effective ML experimentation.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
- Drive improvements in researcher and ML developer productivity and enable new ML use cases through advancements in internal tooling and scheduling infrastructure.
- Lead efforts to optimize Machine Learning development processes at Google, focusing on reducing bottlenecks and building solutions to radically increase developer velocity on timelines, including improvements in code building, packaging, and TPU scheduling.
- Provide technical leadership and mentorship, particularly for new London team members, while fostering a collaborative, inclusive, and innovative team environment that encourages knowledge sharing and growth.
- Develop and execute plans by collaborating with Google DeepMind and internal partners to build relationships, understand user needs, prioritize work, identify emerging research areas, and translate them into practical solutions.
- Write product or system development code and participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
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