Staff Software Engineer, AI Engines 3P TPU Inference

MINIMUM QUALIFICATIONS:

* Bachelor’s degree or equivalent practical experience.

* 8 years of experience in software development.

* 5 years of experience testing, and launching software products, and 3 years

of experience with software design and architecture.

* 5 years of experience with one or more of the following: Speech/audio (e.g.,

technology duplicating and responding to the human voice), reinforcement

learning (e.g., sequential decision making), ML infrastructure, or

specialization in another ML field.

* 5 years of experience with ML design and ML infrastructure (e.g., model

deployment, model evaluation, data processing, debugging, fine tuning).

PREFERRED QUALIFICATIONS:

* Master’s degree or PhD in Engineering, Computer Science, or a related

technical field.

* 8 years of experience with data structures and algorithms.

* 3 years of experience in a technical leadership role leading project teams

and setting technical direction.

* 3 years of experience working in a complex, matrixed organization involving

cross-functional, or cross-business projects.

* Experience with TPUs, TPU system design, and GPUs.

* Expertise in ML compilers and runtimes.

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.

With your technical expertise you will manage project priorities, deadlines, and

deliverables. You will design, develop, test, deploy, maintain, and enhance

software solutions.

As a Staff Software Engineer, you will have expertise in ML compilers and

runtimes. You will have management and leadership experience and strong

partnership skills to enact impact leveraging cross-organizational technical

collaborations.

This organization provides ML infrastructure for all of Google. In close

partnership with Research, this organization delivers the Gemini models, and

drives their usage within and outside Google. Within this organization, the

Machine Learning Infrastructure Runtime and API teams mission is to deliver

highly performant, modular and scalable ML software infrastructure.

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.

Individual pay is determined by factors including job-related skills,

experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google

[https://www.google.com/about/careers/applications/benefits/].

RESPONSIBILITIES:

* Exercise judgment to guide sustainable engineering choices for ML systems at

scale.

* Innovate next directions for infrastructure over a 12-month time horizon

given a rapidly changing technology landscape.

* Deliver impactful capability and optimization impact to Cloud and partner

product areas.

* Migrate existing frameworks (TensorFlow, JAX, PyTorch) runtimes (TF Executor,

TFRT, PJRT) and product areas custom workflows (AdBrain) onto ML Runtime,

minimizing any user disruption.

* Partner with GDM to transfer key innovations into products developed by your

team and partner teams.