Jobs

Scholarships

Courses

Companies

Placements

Community

Home >

Jobs >

Software Engineer, ML Compilers, Silicon

Software Engineer, ML Compilers, Silicon

3 Hours ago • 1 Years + • Research & Development • Artificial Intelligence

About the job

4 skills required for this role

Test your skills to join the top 1% applicants for this job

cpp

algorithms

data-structures

networking

Job Description

Google is seeking a Software Engineer to develop ML compilers for Tensor TPUs, accelerating Generative AI and other machine learning models on custom hardware. Responsibilities include building compilers and tools that map ML models to hardware ISA, evaluating parallelization strategies (performance, power, energy, memory), collaborating with ML researchers and hardware engineers, and managing project priorities. The ideal candidate possesses experience in C++, data structures, algorithms, and ideally, compiler experience and knowledge of parallel hardware. The role focuses on always-on computing use cases and contributes to Google's mission of making information universally accessible.

Must have:

C++ or other programming languages
Data structures and algorithms
Build ML compilers and tools
Evaluate parallelization strategies
Collaborate with researchers and engineers

Good to have:

Master's degree in CS/CE
Power and performance optimizations
Compiler experience
Parallel hardware knowledge

Not hearing back from companies?

Unlock the secrets to a successful job application and accelerate your journey to your next opportunity.

Minimum qualifications:

Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience.
1 year of experience in C++ or other programming languages.
Experience in data structures and algorithms.

Preferred qualifications:

Master's degree in Computer Science or Computer Engineering, or a related field.
Experience in power and performance optimizations.
Experience with compilers.
Knowledge of hardware that provides a high degree of parallelism.

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.

Google's mission is to organize the world's information and make it universally accessible and useful. The team combines Google AI, Software, and Hardware to create helpful experiences. In this role, you will research, design, and develop new technologies and hardware to make computing faster. The team's goal is to make people's lives better through technology.

As a Software Engineer, you will work on developing ML compilers for the Tensor TPU to accelerate Generative AI and other machine learning models running on custom hardware accelerators. You will manage project priorities, deadlines and deliverables.

Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.

Responsibilities

Build compilers and tools that map ML models, with a focus on always-on computing use cases, to the hardware ISA.
Evaluate various trade-offs of different parallelization strategies such as performance, power, energy, and memory consumption.
Collaborate with machine learning researchers to improve the domain-specific compiler.
Collaborate with hardware engineers to evolve future accelerators.

View Full Job Description

Upload your resume, increase your shortlisting chances by 80%

About The Company

Google

2315 Active Jobs

A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.