Remote Math Problem Solving Jobs in San Francisco, CA

JITX is revolutionizing circuit board design by making it code-first. Instead of dragging components around in a GUI, engineers write code (or have AI write it for them) to define their circuit boards. Our solvers handle the low-level details, making hardware engineering massively reusable. We're a ~12-person startup building tools that bring software engineering practices to hardware design.

We're looking for a senior software engineer with a strong mathematical and algorithmic foundation who can own significant product areas end-to-end. You'll work on hard computational problems, from design automation algorithms to real-time visualization, shipping features that directly impact how electrical engineers design the hardware that powers the world.

You'll be diving straight into our new simulation loop project, a core initiative that tightly integrates our design engine with circuit simulation to catch errors earlier and give engineers faster feedback.

Design Automation Algorithms

- Placement, routing, pin-assignment, and geometry generation algorithms for PCBs
- Computational geometry and spatial data structures
- Constraint solving and optimization

Simulation Integration
- Integrating industry simulation tools (e.g. Ansys HFSS) into our design flow
- Building feedback loops that drive automated design optimization using simulation results
- Bridging between our design engine and external solvers to enable closed-loop iteration

Must Haves
- Strong algorithmic problem-solving skills: graph/tree data structures, computational efficiency, and parallelism
- Mathematical maturity. Comfortable reasoning formally about geometry, linear algebra, or optimization
- Solid software engineering fundamentals
- Ability to see the big picture and understanding how your work fits into the overall product
- Self-directed work style with ability to unblock yourself and others
- Track record of owning large features from planning through production
- Comfortable working with ambiguity in a startup environment

Nice to Haves
- Background in computational geometry, spatial data structures, or geometric algorithms
- Polyglot programming experience, comfortable across multiple languages and paradigms
- Interest in hardware, electronics, or CAD tools
- Education in Computer Science, Physics, Mathematics, or comparable industrial experience

You're an experienced software engineer with a strong mathematical foundation who knows that startups offer the best combination of impact and interesting problems to solve.

You think algorithmically. You're comfortable reasoning about complexity, working through geometric and graph problems, and finding elegant solutions where brute force won't cut it. You have the mathematical maturity to formulate problems precisely before reaching for an implementation, whether that's a placement algorithm, a constraint solver, or a simulation feedback loop.

You're an engineer first. You write clean, consistent, production-ready code and take ownership of features end-to-end. You think about reliability and staging from the start, not as an afterthought.

You thrive when given ownership of a problem space. You're the person who asks "why are we building this?" before diving into "how should we build it?" You don't need your hand held, but you're not afraid to raise your hand when you need context or when you spot a problem with the plan.

- The algorithms we're building don't exist yet. Fully automated PCB layout (with placement, routing, pin assignment, and now simulation-in-the-loop) is an open research problem that we're turning into a shipping product.
- Hardware is everywhere. The tools engineers use to design it haven't fundamentally changed in decades. We're changing that.
- Because our designs are code, we have a natural foundation for AI that traditional GUI-based tools simply don't. We can leverage AI at every stage in ways that aren't practical when designs live in proprietary formats.
- You'll work directly with the people making architectural decisions, not through layers of process.
- We care about elegant solutions, not just working ones.

- **Code Framework:** Python
- **Runtime:** Some legacy code in a custom language (Stanza) and C++; we're actively replacing Stanza and you would be part of shaping that decision.
- **UI:** TypeScript, React, PixiJS (transitioning toward Three.js/WebGL)
- **Simulation:** Ansys HFSS and other EDA/EM solvers (integrated via our simulation loop)
- **Deployment:** Application installed on the user's machine, possibly airgapped. Architected to support headless and remote.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.