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.

The Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers.

The US base salary range for this full-time position is $174,000-$252,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Support new and exciting Machine Learning (ML) paradigms, such as horizontal scaling for upcoming TPU chips, by making contributions across the end-to-end stack and analysis tools.

• Learn and build an intuitive understanding of existing data collection, analysis, and visualization workflows.

• Understand model optimization use-cases, drive cross-functional efforts to deliver on chip-profiling requirements, and propose new hardware features.

• Collaborate across hardware, driver, runtime, and performance analysis teams and other key stakeholders.

• Collect and analyze profile data to provide expert-level visualizations and user-actionable advice.

Minimum qualifications

• Bachelor’s degree or equivalent practical experience.

• 5 years of experience in the machine learning field.

• 5 years of coding experience in one or more of the following languages: C, C++, Java, or Python.

• 2 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.

• 1 year of experience with GPU programming.

• Experience with engineering tools and infrastructure.

Preferred qualifications

• Master's degree or PhD in Computer Science or a related technical field.

• 2 years of experience with data structures and algorithms.

• Experience with GPU or TPU performance analysis, and a drive for developer productivity.

• Experience with ML frameworks such as Tensor Flow, JAX, and Py Torch, or ML compilers such as Accelerated Linear Algebra (XLA).

• Experience in open-source software development, including releasing and supporting open-source projects.

• Experience developing accessible technologies.