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

Open nowPosted 79 days ago

ML Infra Engineer, Data Systems — Physical Intelligence

Accel portfolio7,376 open roles

Where
San Francisco, CA, USA
Work mode
On site
Get the CV for this job

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

Your applicationOpen nowML Infra Engineer, Data Systems — Physical IntelligenceAccel portfolio · San Francisco, 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 Accel portfolio'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.

8.5% of postings close within 7 days. Measured by our own scanner across the market. Accel portfolio postings stay open a median of 28 days.

Share of postings closed within
  1. 1.8%1 day
  2. 4.0%3 days
  3. 8.5%7 days
  4. 15.4%14 days
  5. 34.1%30 days
This job: posted 79 days ago

Accel portfolio median: 28 days open

The posting

Physical Intelligence is bringing general-purpose AI into the physical world. We are a group of engineers, scientists, roboticists, and company builders developing foundation models and learning algorithms to power the robots of today and the physically-actuated devices of the future.

As an ML Infra Engineer (Data Systems), you’ll build and operate the data infrastructure that powers large-scale robot learning. Your systems will sit directly between raw data sources and training/evaluation, enabling us to move faster while maintaining performance, correctness, and reliability at scale.

This is a systems role at the intersection of distributed systems, storage, and machine learning infrastructure.

The Team

The Infrastructure organization builds the foundations that make large-scale learning possible at PI. This includes training systems, data platforms, evaluation pipelines, and the tooling that allows researchers and roboticists to work with massive datasets safely and efficiently.

In This Role You Will

  • Data Ingestion & Processing: Design and build high-throughput pipelines that validate, transform, and featurize raw multimodal data.
  • Batch & Streaming Systems: Operate large-scale batch and streaming workflows over massive datasets.
  • Storage Systems: Design object storage layouts, metadata systems, and efficient access patterns; choose file formats with performance and scalability in mind.
  • Data Lifecycle Management: Build systems for backfills, dataset rebuilds, garbage collection, and large-scale transformations.
  • Training-Time Performance: Optimize dataloaders, sharding, prefetching, caching, and throughput to reduce time from data arrival → model training.
  • Metadata & Indexing: Build scalable metadata stores for datasets, annotations, and training artifacts.
  • Data Movement: Move petabytes efficiently across clusters and environments.
  • Operational Correctness: Implement observability, validation, and guardrails to prevent silent data regressions.
  • Cross-Functional Collaboration: Work closely with cross-functional teams of researchers, engineers and roboticists to translate evolving data needs into robust systems.

What We Hope You’ll Bring

  • Strong software engineering fundamentals.
  • Experience building distributed systems or large-scale data pipelines.
  • Comfort reasoning about performance, memory, I/O, and storage efficiency.
  • Familiarity with batch and/or streaming processing systems.
  • Experience with object storage systems and data format tradeoffs.
  • Ownership mindset: design, build, operate, and iterate on systems end-to-end.
  • Enjoy working closely with researchers and unblocking fast-moving projects.

Bonus Points If You Have

  • Experience with large ML training pipelines or dataloading systems.
  • Knowledge of columnar or custom data formats.
  • Experience with systems like ClickHouse, Ray, Flink, Spark, or similar.
  • Hands-on experience operating petabyte-scale datasets.
  • Debugging and fixing performance bottlenecks in data-heavy systems.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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 Accel portfolio'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 Accel portfolio'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

    Accel portfolio'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.