Runtime Engineer at MatX

Mountain View, California, United States -

Full Time

Start Date

Immediate

Expiry Date

25 Aug, 26

Salary

475000.0

Posted On

27 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Rust, C++, C, Go, Python, PyO3, CUDA, ROCm, oneAPI Level Zero, TPU, Memory Management, FFI/ABI, LLM Inference, Device Memory Management, DMA, Cluster Orchestration

Industry

Computer Hardware Manufacturing

Description

What MatX is Building MatX is building custom silicon for large-language-model inference and training, with HW/SW co-design across ISA, RTL, simulator, compiler, and kernels so each layer benefits from the others. The runtime owns the host-side stack and the contracts that bind those teams together. What You'll Do Here Build the host-side interface library — device memory management, DMA, streams and events, sync primitives — that every compiler-emitted program runs on top of Own and extend the executable format: the compiler→runtime contract, its versioning, the weight and quantization layouts that let compiler and runtime evolve independently Design the custom-kernel ABI — calling convention, sync semantics, lifecycle — and the host-side marshaling layer (DLPack, the buffer protocol, numpy) that gets Python tensors to the device Build Python bindings via PyO3, with a C-ABI shim as the alternative integration path for downstream consumers Build the LLM inference serving stack — paged KV cache, continuous batching, request scheduling, token streaming — and the cluster orchestration primitives underneath it Bring up interconnect topology from the host and own the failure-detection and clean-teardown path for stop-restructure-resume recovery across racks Design what the chip exposes to host-side profilers and debuggers — perf counters, traces, and the Python surfaces ML engineers actually use — and hit measurable performance targets on runtime overhead and serving throughput Who You Are Strong experience in a systems programming language — Rust, C, C++, or Go — including memory management, allocator design, and FFI/ABI work Have built Python interop layers in production (PyO3, ctypes, pybind11, or equivalent C-ABI bridging) Have designed and maintained API or ABI contracts between teams — versioning, evolution, breaking-change discipline — not just consumed someone else's Hands-on with at least one accelerator programming model (CUDA, ROCm, oneAPI Level Zero, TPU, or comparable) — enough to reason about device memory, async execution, and kernel launch ML-systems literate — comfortable with the training and inference loop, what collectives do, what a tensor layout is. Research depth not required. Bonus Points If You Have LLM inference internals — vLLM, TensorRT-LLM, or SGLang (paged attention, scheduler design) Rust at depth, including proc macros, unsafe with soundness reasoning, and complex lifetime/trait work Custom allocator design (slab, paged, arena) or other low-level memory work ML framework integration experience (PyTorch custom backends, JAX/XLA, ONNX runtime) Profiler or tracing infrastructure work (perfetto, Nsight, or a custom stack) Driver-adjacent or kernel-bypass work, or prior new-silicon bring-up Compensation The US base salary for this full-time position is determined based on a variety of factors including role, experience, location, job related skills, and relevant education and training. Career length is only a guideline for compensation. Early Career - $120,000 - $250,000 + equity Mid Career - $175,000 - $362,500 + equity Senior Career - $250,000 - $475,000 + equity What We Offer A Stake in our success Generous equity, with option cash/equity swap at offer, and option to employee early exercise. Health & Wellness Company subsidized Health, Dental, Vision, and Life insurance; Pre-tax Health Savings Accounts with generous company contribution (even if you don’t) Time To Recharge 4 weeks paid time off (accrued), 12 company holidays, and 3 weeks remote/flexible work per year Support to Parents Up to 12 weeks of paid parental leave, regardless of your path to parenthood Learning & Development $1,500 yearly towards your professional development e.g. conferences, courses, and other learning opportunities Team Connection Team Lunches, quarterly off-sites, and regular town halls Financial Wellbeing. 401K and/or Roth IRA, with 5% company contribution, even if you don’t! Flexible Spending Accounts Pre-tax spend accounts for medical, dental/vision, dependent care, parking, and transit expenses Commute On Us For those commuting up to 1 hour, put your rideshare cost on our company card and reclaim the drive-time to get work done! MatX E[x]tras $50 per month to use on the perks you care about most Remote Perks We work remotely Monday & Friday, supported by home-tech setup, and remote wifi expense reimbursement As part of our dedication to the diversity of our team and our focus on creating an inviting and inclusive work experience, MatX is committed to a policy of Equal Employment Opportunity and will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin or ancestry, sex, gender, gender identity, gender expression, sexual orientation, age, physical or mental disability, medical condition, marital/domestic partner status, military and veteran status, genetic information or any other legally recognized protected basis under federal, state or local laws, regulations or ordinances. This position requires access to information that is subject to U.S. export controls. This offer of employment is contingent upon the applicants capacity to perform job functions in compliance with U.S. export control laws without obtaining a license from U.S. export control authorities. MatX does not accept unsolicited resumes from individual recruiters or third-party recruiting agencies in response to job postings. No fee will be paid to third parties who submit unsolicited candidates directly to our hiring managers or People team and any resumes submitted are deemed to be the property of MatX.

Responsibilities

Build the host-side interface library and executable format for custom silicon designed for LLM inference and training. Develop the LLM inference serving stack, including paged KV cache and cluster orchestration primitives.