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

Open nowPosted 98 days ago

Member of Technical Staff — Inference-Multi-Hardware

RadixArk20 open roles

Pay
$200,000 – $400,000 a year
Where
Palo Alto, CA
Get the CV for this job

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

Your applicationOpen nowMember of Technical Staff — Inference-Multi-HardwareRadixArk · Palo Alto, 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 RadixArk'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.

13.7% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.3%1 day
  2. 4.8%3 days
  3. 13.7%7 days
  4. 22.1%14 days
  5. 37.6%30 days
  6. 59.1%60 days
This job: posted 98 days ago

The posting

About the Role

RadixArk is seeking a Member of Technical Staff - Inference-Multi-Hardware to push the limits of performance for frontier AI systems.

Most performance engineering assumes a single vendor's stack. This role assumes none. You'll bring up, optimize, and maintain SGLang, Miles, and the RadixArk infrastructure stack across NVIDIA and AMD GPUs, Google TPUs, modern server CPUs, and a growing set of emerging AI accelerators. That means porting kernels and runtimes onto unfamiliar hardware, designing the abstractions that keep one codebase fast on all of it. You will be working directly with silicon and our partners, often on pre-release platforms with immature tooling.

This is one of the broadest technical roles at RadixArk. The problem changes shape with every new platform: a memory hierarchy that punishes your last set of assumptions, a compiler that fuses differently, a collective library that doesn't exist yet. We're looking for engineers who find that appealing rather than exhausting, and who can go deep on a new architecture fast without losing the performance instincts they built on the last one.

Requirements

  • 4+ years of experience in systems, performance, or ML infrastructure engineering
  • Deep expertise in at least one accelerator programming model (CUDA, ROCm/HIP, Pallas/XLA, Triton, or a vendor SDK), with demonstrated ability to pick up new ones quickly.
  • Strong understanding of accelerator architecture: memory hierarchy, bandwidth limits, occupancy, and the tradeoffs between them
  • Experience writing or optimizing high-performance kernels for ML workloads
  • Experience with distributed execution and communication libraries (NCCL, RCCL, MPI, or equivalents)
  • Proficiency in C++ and Python
  • Strong debugging and profiling skills at the system level, including on platforms where the tooling is incomplete or unreliable
  • Track record of performance work that shipped into production

Strong Plus

  • Experience bringing up ML workloads on new silicon.
  • Hands-on depth in more than one vendor ecosystem
  • Experience with compiler stacks (XLA, MLIR, TVM, Triton) or building compiler passes and IR transformations
  • Experience designing hardware abstraction layers or portable kernel interfaces
  • Quantization and mixed-precision work across differing numeric formats and hardware support levels
  • Experience with distributed inference systems (SGLang, vLLM) or training/RL frameworks (Miles, Megatron, veRL, TorchTitan)
  • CPU inference optimization (AVX-512/AMX, oneDNN, NUMA-aware execution)
  • Experience optimizing collective communication at scale, or scaling workloads to 1000+ accelerators
  • Contributions to kernel, compiler, or ML systems open source
  • Direct collaboration with silicon vendors or cloud partners on technical evaluations
  • Background in HPC or other performance-critical systems

Responsibilities

  • Bring up RadixArk's inference and training systems on new accelerator platforms and drive them to competitive performance
  • Design hardware abstractions that let a single codebase stay fast across vendors without forking
  • Port and optimize kernels across programming models and memory architectures
  • Build cross-platform benchmarking, profiling, and regression detection so performance claims hold up on every target
  • Debug numerical divergence and correctness gaps between platforms
  • Work with vendor engineering teams on pre-release hardware, compiler and driver issues, and roadmap feedback
  • Partner with kernel, runtime, distributed systems, and product engineers to land performance wins end to end
  • Serve as the internal source of truth on what each platform is actually good at
  • Contribute hardware-specific optimizations, benchmarks, and portability work back to open-source SGLang and Miles

About RadixArk

RadixArk is an infrastructure-first company built by engineers who've shipped production AI systems, created SGLang (30K+ GitHub stars, the fastest open LLM serving engine), and developed Miles (our large-scale RL framework). We're on a mission to democratize frontier-level AI infrastructure by building world-class open systems for inference and training. Our team has optimized kernels serving billions of tokens daily, designed distributed training systems coordinating 10,000+ GPUs, and contributed to infrastructure that powers leading AI companies and research labs. We're backed by well-known infrastructure investors and partner with Nvidia, Google, and frontier AI labs. Join us in building infrastructure that gives real leverage back to the AI community.

Compensation

Depending on background, skills, and experience, the expected annual salary range for this position is $200,000 - $400,000 USD + equity.

Equal Opportunity

RadixArk is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

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 RadixArk'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 RadixArk'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

    RadixArk'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.