Skip to content
CV Rocket
Get started
How it worksThe enginePricingBlogContactSign in

Open nowFirst seen 8 hours ago

Software Engineer III, AI/ML, TPU Efficiency, YouTube

Google3,315 open roles

Where
Mountain View, CA, USA
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowSoftware Engineer III, AI/ML, TPU Efficiency, YouTubeGoogle · Mountain View, CA, USA

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on Google's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

8.1% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 26 days.

Share of postings closed within
  1. 1.7%1 day
  2. 3.6%3 days
  3. 8.1%7 days
  4. 15.1%14 days
  5. 34.0%30 days
This job: first seen 8 hours ago

Google median: 26 days open

The posting

In most instances, this position requires in-person interviews as part of the hiring process.

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 2 years of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).
  • 2 years of experience with accelerator hardware architectures (TPUs/GPUs).
  • 2 years of experience programming in C++ and Python.
  • Experience with ML frameworks such as TensorFlow, JAX, and PyTorch, or ML compilers (e.g., accelerated linear algebra (XLA)).
  • Experience with ML model optimization.

Preferred qualifications:

  • Master's degree or PhD in Computer Science or related technical fields.
  • Experience developing accessible technologies.
  • Experience with debugging correctness and performance issues at all levels of the ML software stack.
  • Experience with ML compilers and their internals, experience writing compiler optimization passes.

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 part of this team, you will own the optimization of the models powering the YouTube algorithm. Your work will focus on model efficiency optimization, such as low-precision quantization , knowledge distillation, parameter sharing, and designing hardware-friendly model architectures, to reduce training and serving costs while maximizing fleet utilization and value delivered to users.

You will build support and optimize new and existing models in our Recommendation System stack, including new model architectures while adapting to next-generation TPU hardware.

You will engage in model and TPU compiler co-design, with opportunities to work across the stack ranging from end-user ML models down to Hardware/Software architecture. At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Analyze ML workloads, identify compute and memory bandwidth bottlenecks, and optimize accelerator utilization to maximize compute efficiency.
  • Explore, implement, and productionize algorithmic efficiency techniques, including low-precision quantization, knowledge distillation, parameter sharing, and attention optimizations.
  • Optimize auxiliary serving and distributed data pipelines, including data ingestion, feature transformation, embedding lookups, and memory caching to support real-time training and inference.
  • Collaborate with ML model developers and researchers to co-design hardware-friendly model architectures and deploy universal efficiency libraries.
From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against Google's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on Google's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    Google's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

Get the CV for this job
By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.