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

Open nowFirst seen 2 hours ago

Production Systems Engineer, Hardware Analytics

Meta1,073 open roles

Where
Menlo Park, CA
Get the CV for this job

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

Your applicationOpen nowProduction Systems Engineer, Hardware AnalyticsMeta · Menlo Park, CA

  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 Meta'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.

8.2% of postings close within 7 days. Measured by our own scanner across the market. Meta postings stay open a median of 35 days.

Share of postings closed within
  1. 1.8%1 day
  2. 3.6%3 days
  3. 8.2%7 days
  4. 15.2%14 days
  5. 34.0%30 days
This job: first seen 2 hours ago

Meta median: 35 days open

The posting

Meta is seeking a Production Systems Engineer to join our Hardware Design and Release to Production - Sustaining (HDRTP) team. Our servers and data centers are the foundation upon which our rapidly scaling infrastructure operates efficiently to deliver our innovative services. The HDRTP team is responsible for the end-to-end Hardware Lifecycle of all Meta servers, from exploration and development to production health. HDRTP Engineers work closely with Production Engineering teams, Networking, Hardware Designers, Networking Teams, Manufacturers, Vendors, Datacenter Operation, Capacity, Core Systems and New Product Introduction teams to ensure the smooth operation of systems globally.

Responsibilities

  • Drive innovation in hardware efficiency by applying expertise in hardware reliability and performance, and translating insights into actionable strategies for hardware reliability and data center optimization
  • Contribute to industry leading research in hardware characterization and fleet/DC efficiency studies across AI platforms, leveraging data-driven and machine learning analytical techniques
  • Conduct in-depth hardware parameter based research and comparative analyses using advanced data analytics and machine learning techniques for failure analysis and diagnosis in production
  • Interface with internal hardware, software engineers and operations teams to understand system architectures and failure modes
  • Proactively create experiments, data analysis and data visualizations to detect and diagnose hardware health issues, focusing on systemic solutions
  • Collaborate on evolving AI platforms, silicon products, thermal and cooling solutions to support the growth of large language models, with a focus on optimizing performance, scalability, and efficiency
  • Develop data frameworks and discover insights to answer relationship between hardware, data center parameters and server failures
  • Develop and implement data-driven strategies using hardware characterization studies to support hardware fleet optimizations and efficiency while supporting improvements to future platform designs
  • Build comprehensive monitoring and predictive frameworks and to make data insights available to partner teams for decision making
  • Collaborate with cross-functional teams to ingest and present data on evolving domains and specialized hardware technologies, components, datacenters
  • Share insights with stakeholders and software teams to develop architectures to handle server failures based on hardware health data
  • Troubleshoot, diagnose and root cause of system failures and isolate the components or failure scenarios with in depth statistical studies while working with stakeholders internally and externally

Minimum Qualifications

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • 8+ years of hands-on software/firmware/hardware engineering to build systems/products for the IT industry
  • Troubleshooting and data tooling, including data analysis, building analytical models, and visualizations
  • Knowledge of server architecture and components across Compute/Storage/AI Systems/Networking

Preferred Qualifications

  • Experienced in the integration of lab tools for automated workflows
  • Experience with Linux systems and server systems management
  • Master’s degree or PhD in Computer Engineering, Electrical Engineering, or related field
  • Proficient in SQL, Python or C/C++ (data structures, algorithms, and OOP)
  • Experience with some of the following modules/domains: PCIe, Networking, Flash, Memory, CPU, GPU, DRAM (DDR4/5 or HBM)

US: $173,000/year to $245,000/year + bonus + equity

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 Meta'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 Meta'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

    Meta'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.