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Skills
Nice to have
Requirements
Minimum qualifications:
- Bachelor's degree in Computer Science, a related technical field, or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages (e.g., C++, C, or Python).
- Experience in leading cross-functional software oriented projects from inception to delivery.
Preferred qualifications:
- 5 years of experience with data structures and algorithms.
- Experience with ML frameworks (e.g., TensorFlow, JAX, PyTorch) and hardware performance analysis, particularly with TPUs and GPUs.
- Experience with Compilers and Compiler construction.
- Experience programming in Python.
- Ability to effectively navigate and communicate in a fast-paced environment.
The role
The Core ML team contributes to frameworks and compilers that support the Google Cloud Platform (GCP) Cloud TPU service and related ML models/frameworks. It provides ML infrastructure customers (both external and internal to Google) with large-scale, cloud-based access to Google's first-party ML supercomputers (TPUs and TPU Pods) to run training and inference workloads using PyTorch and JAX.
The PyTorch TPU team is responsible for the PyTorch ML framework/processes/ecosystem/model performance, as well as engagements with customers who take advantage of Google's TPUs to achieve massive scale and speed in their ML workloads.Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's 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
- Work on AI framework development to successfully enable PyTorch models to run on Google Cloud's Tensor Processing Units (TPUs) and Graphics Processing Units (GPUs) and tune for peak performance.
- Provide comprehensive support for ML frameworks and compilers on Cloud TPUs and GPUs, enabling the training and deployment of the most advanced machine learning models, driving innovation and breakthroughs.
- Enable PyTorch models at massive scale for generative models, computer vision (image recognition, object detection, image generation), machine translation, language modeling, rankings and recommendations, speech recognition, etc.
- Collaborate with other Google teams and leading researchers across the industry to continuously bring ML capabilities to our PyTorch-in-Cloud offering.
- Contribute to open-source software development.
Hiring process
Apply online
Assessments
Online test · Not every role
You may be asked to take the Google Hiring Assessment (workstyle skills) and, for some roles, role-related assessments such as a coding exercise.
Recruiter conversations
With a recruiter · Phone call · 1–2 sessions
One or two shorter conversations assessing key skills, sharing information about the organisation and team, and asking about your preferences such as location.
Project work
In your own time · Not every role
For some roles, a small project before interviews: a case study, writing or code samples.
Interviews
With a rotating cast of Googlers
A panel of structured interviews, over video or in person, with a rotating cast of Googlers; open-ended role-related questions scored against the same rubric for every candidate, no brainteasers.
Decision and offer · With a recruiter
- Structured interviews: every candidate for a role is scored against the same rubric; no brainteasers.
- AI tools are not permitted during interviews.
- For some roles, pre-selected interviews happen virtually before final interviews onsite.
About Google
- Industry
- Technology
- Founded
- 1998
- Employees
- 100,000+
- Headquarters
- Mountain View, USA
- Website
- google.com
Location
Google · London
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