Applied Math Libraries Engineer (SPU)

Benefits

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Work mode

Onsite From the posting source checked Jun 20, 2026

In-office days

5 days From the posting source checked Jun 20, 2026

Schedule

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Weekend work

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Company

Company stage

Early From the posting source checked Jun 20, 2026

Application

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Deadline

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State eligibility is not yet verified.

About this role

Applied Math Libraries Engineer (SPU) Redwood City | OnSite Vorticity is building the world's first Scientific Processing Unit (SPU https://pyrite9.com), a new class of silicon purpose-built to accelerate scientific computing beyond the limits of GPUs. We are designing tightly coupled software-hardware systems around applied mathematics workloads to deliver order-of-magnitude performance gains. Unlocking its full potential requires early, deep engagement from applied mathematics-driven software engineers who can translate real-world scientific workloads into executable models, kernels, libraries, and applications that inform both architecture and tooling decisions. As a Applied Math Libraries Engineer, you will work at the intersection of applied mathematics, scientific computing, and low-level software. From day one, you will help build the numerical software foundation of the SPU. This role is focused on building reusable mathematical primitives rather than full end-to-end scientific applications. The ideal candidate is excited to implement mathematics on a new architecture. You will work closely with hardware architects, compiler engineers, and runtime engineers to shape how numerical algorithms are expressed, executed, and optimized on the SPU. This position is ideal for someone who enjoys moving fluidly between applied math, numerical algorithms, and low-level software, and who wants to help build a new scientific computing platform from the ground up. RESPONSIBILITIES - Prototype and implement core numerical linear algebra kernels and libraries for the SPU. - Translate mathematical algorithms into executable, performance-relevant software. - Write C, C++, and Python reference implementations to guide hardware, compiler, and runtime decisions. - Design benchmarks, correctness tests, numerical accuracy tests, and

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