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Machine Learning GPU Performance Engineer

Posted: 02/10/24
Recruiter:The Learning Experience
Reference:2828644398
Type:Permanent
Disciplines: Systems Engineer
Salary:Competitive
Location:London
Description: Machine Learning GPU Performance Engineer Google

Published 20 Aug 2024

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London

Full Time

27500 - 275000 people

Role Highlights

C++

Python

Triton

AI

Data Analysis

NLP

Information Retrieval

Computer Science

Full Stack

Software Design

Data Structures

System Design

Technical Leadership

Testing

PhD

Search

Storage

Security

UI

Infrastructure

LLMs

Tools, Libraries and Frameworks

XLA

GPUs

Description

Google's software engineers develop next-generation technologies that change how billions of users connect and interact with information. The role involves working on projects critical to Google's needs, providing opportunities for switching teams as the business evolves. Engineers are expected to demonstrate versatility and leadership qualities while tackling new problems across the full-stack. The Core team builds foundational technical components and engages with product teams to enhance model performance and efficiency at a massive scale.

At gTech's Users and Products team, innovations are focused on enhancing user engagement and solving complex customer needs through technical expertise and a deep understanding of Google's and Alphabet's broad product environments. The team acts as a bridge between Google's users and its product teams, ensuring that user insights are integrated into product offerings which support numerous annual product launches. The newly formed Machine Learning Data Operations (MLDO) team within gUP Operations plays a critical role in delivering and tuning machine learning and GenAI data operations across Google's product suite, leveraging extensive global vendor networks. Google's overarching goal is to create impactful products and services, with gTech playing a strategic role in bringing these solutions to fruition through technological and operational expertise.

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