Skip to content

Open nowPosted 3 days agoWe saw it 42 min after it went up

Compiler Backend Engineer

Normal Computing37 open roles

Pay
$200,000 – $300,000 a year
Where
Mountain View
Work mode
Hybrid
Get the CV for this job

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

Your applicationOpen nowCompiler Backend EngineerNormal Computing · Mountain View
  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 Normal Computing'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.

11.8% of postings close within 7 days. Measured by our own scanner across the market. Normal Computing postings stay open a median of 63 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: posted 3 days ago

Normal Computing median: 63 days open

The posting

NORMAL COMPUTING | BUILD WITH US

Normal is an applied AI company solving the hardest problems in AI and silicon. We build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world, in partnership with the world's most advanced institutions. We work as one team across New York City, Silicon Valley (Mountain View), London, Copenhagen, and Seoul.

THE ROLE

Normal's hardware runs the most memory-bound parts of large-model inference inside memory itself, rather than shuttling weights to a processor. The software that makes this programmable doesn't exist yet in any standard form. Getting a model correct on that hardware is the frontend's job; making it fast is yours. Our hardware does not look like a CPU or GPU, so its compiler backend can't be borrowed from one. As a Compiler Engineer focused on the backend, you will help design and build the custom compilation that maps LLM inference onto it, from scheduling and memory planning to the code our hardware actually executes.

You will work at the boundary between the compiler and the hardware, closely enough to know when an optimization belongs at a different layer, or when the right answer is a new abstraction. Our chip is pre-silicon, so you will measure your work against our simulators and FPGA prototypes first, and against silicon as it arrives.

WHAT YOU WILL OWN

- Code Generation: Build the passes that turn lowered programs into the code our hardware executes, designing new compilation approaches where conventional ones don't fit. Success means correct, efficient code for every operation our models need.

- Scheduling and Memory Planning: Own how work and data are scheduled and placed across our hardware's resources, measured by utilization and end-to-end latency on LLM inference.

- Fusion and Dispatch: Own fusion and dispatch decisions for LLM inference, so the hardware spends its time computing rather than moving data.

- Hardware Co-Design: Work the abstraction layer between the compiler and the hardware, and feed compiler constraints back to our hardware architects while the design can still change.

- Profiling and Validation: Validate every optimization with measured results from simulators, FPGA prototypes, and then silicon, and maintain a performance regression suite the team trusts.

- Cross-Team Handoffs: Take lowered programs from our frontend compiler engineers, and decide with the team which operations the compiler generates and which use hand-tuned kernels.

WHAT MAKES YOU A GREAT FIT

- Deep experience with compiler optimization or code generation for accelerators or other non-CPU targets: scheduling, tiling, fusion, or resource allocation

- Comfort working close to hardware: you think in terms of memory bandwidth and utilization as well as asymptotic complexity

- Willingness to design compilation approaches from first principles when existing ones don't fit the hardware

- Track record of shipping optimizations that moved a measured performance number

- Comfort building software for hardware that is still evolving, from simulation through bring-up

- Fluency in Python, and familiarity with C, C++, or Rust

BONUS POINTS

- Experience with PyTorch's compilation stack (TorchDynamo, FX, Inductor, torch.export) or other ML compilers, such as IREE, TVM, or XLA

- Experience compiling for in-memory, spatial, or other non-von-Neumann compute targets

- Background in hardware design tools such as logic synthesis or place-and-route

- Experience building or using cycle-level or performance simulators to guide optimization decisions

- Contributions to open-source compiler or kernel infrastructure (e.g., PyTorch, Triton, TVM, MLIR, LLVM)

- Publishing or presenting compiler or performance work at venues such as MLSys, ASPLOS, or CGO

Equal Employment Opportunity Statement

Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.

Accessibility Accommodations

Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at [email protected].

Privacy Notice

By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Applicant Privacy Notice https://normalcomputing.com/applicant-privacy-notice.

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 Normal Computing'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 Normal Computing'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

    Normal Computing'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.

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.