About the role

What will you do at Google?

MINIMUM QUALIFICATIONS:

* Bachelor's degree in Computer Science, a similar technical field, or

equivalent practical experience.

* 5 years of work experience in a technical role (e.g., software engineering,

solutions consultant, etc.) or equivalent technical experience.

* 2 years of experience running AI/ML workloads, such as training, fine-tuning,

or serving inference on GPUs or TPUs, including orchestration with Kubernetes

or GKE.

* 2 years of experience producing engaging developer content (e.g., blogs,

short-form videos, podcasts, live streams).

PREFERRED QUALIFICATIONS:

* Experience with AI infrastructure: Kubernetes, GPUs/TPUs and the software

drivers that support them.

* Experience writing and running model-training, reinforcement-learning, or

inference workloads (or clear ability to grow into these).

* Proficiency in Python preferred; strong object-oriented programming in

another language (e.g., C++, Java) acceptable for an "AI-native" applicant

who moves quickly between languages.

* Demonstrated external technical content and public presence (technical blogs,

videos, talks, or popular open-source work — ability to translate complex

hardware workflows (TPU/GPU) into engaging narratives.

* Background in AI development, either building/training models or integrating

generative AI into products.

ABOUT THE JOB:

As a part of the Cloud Developer Relations team, you will join as a Technical

Developer Relations Engineer for our AI Infrastructure team. Your work centers

on the systems that power modern AI that is GKE and Kubernetes, Graphics

Processing Units (GPU) and Tensor Processing Units (TPU) accelerators, and the

drivers and orchestration that keep large training, reinforcement learning, and

inference jobs running at scale.

In this role, you will

be a builder first, to write and run real training,
fine-tuning, and inference workloads, push them to scale on Google's
accelerators, and feed what you learn back to the engineering teams shipping
these products. You will take hard infrastructure problems, the kind that
involve GPU memory limits, TPU topologies, and scheduling and turn them into
demos, blogs, and videos that developers actually want to read and watch.

In this role, you will

bring a real point of view and an audience that listens,
whether built through conference talks, open source, or your own writing about
this space.
The AI and Infrastructure team is redefining what’s possible. We empower Google
customers with breakthrough capabilities and insights by delivering AI and
Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our
customers include Googlers, Google Cloud customers, and billions of Google users
worldwide.
We're the driving force behind Google's groundbreaking innovations, empowering
the development of our cutting-edge AI models, delivering unparalleled computing
power to global services, and providing the essential platforms that enable
developers to build the future. From software to hardware our teams are shaping
the future of world-leading hyperscale computing, with key teams working on the
development of our TPUs, Vertex AI for Google Cloud, Google Global Networking,
Data Center operations, systems research, and much more.
Individual pay is determined by factors including job-related skills,
experience, and relevant education or training.
US: $163000 - $236000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google
[https://www.google.com/about/careers/applications/benefits/].
RESPONSIBILITIES:
* Grow the AI Infrastructure developer community by running programs, events,
workshops, and hackathons that people actually want to attend.
* Collaborate with internal engineering teams, external partners, and
influencers to extend each program's reach and make the case for Google's
platforms.
* Build and maintain the resources developers rely on docs, tutorials, and
sample code and answer their technical questions along the way.
* Dig into the data to spot trends, recurring pain points, and where developers
lose time, then turn that into concrete recommendations for the product
roadmap.
* Represent Google at industry events as a technical voice for our AI tools,
giving talks and live demos.

Which skills does this role require?

C++Machine LearningTechnical WritingPublic SpeakingCloud InfrastructureModel TrainingCloud ComputingGoogle CloudVertex AISoftware EngineeringData CenterGCPLLMsProduct Strategy

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