---
title: 'Fullstack Engineer - Frontend Focus at Inference'
canonical: 'https://feeny.ai/job/fullstack-engineer-frontend-focus-inference-san-francisco-1s8ak7cryhnc'
type: 'job'
last_seen: '2026-09-11'
---

# Fullstack Engineer - Frontend Focus at Inference

- **Company:** Inference
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2025-07-23
- **Last confirmed live:** 2026-09-11
- **Apply:** https://jobs.ashbyhq.com/inference/efe67830-9257-499c-a41c-021c9b96b15f

## Job description

[Inference.net](http://Inference.net) is hiring a Senior Full-Stack (Frontend-Focused) Engineer Help us build beautiful, performant web experiences that give users super-powers over our globally distributed LLM inference platform. If you love shipping React apps that feel snappy at planet-scale, we’d love to meet you.

About [Inference.net](http://Inference.net) We combine idle GPU capacity from around the world into a single cohesive plane of compute capable of serving models like DeepSeek and Llama 4. At any moment, 5,000+ GPUs and hundreds of terabytes of VRAM are connected to our network.

We’re a small, well-funded team working in-person from downtown San Francisco (hybrid flexibility as needed). Investors include a16z CSX and Multicoin. We’re high-agency, collaborative, and obsessed with craft—whether that’s a distributed scheduler or a pixel-perfect UI.

## What you’ll do

- Own the user experience – design, build, and polish the dashboards, consoles, and customer-facing apps that let users observe, configure, and pay for inference at scale.
- Ship end-to-end features – from Figma wireframe to React component to backend API and database migration.
- Design a component system in React + Tailwind that supports rapid iteration and a cohesive design language.
- Optimize performance – SSR, code-splitting, hydration, and WebSocket-driven real-time updates that hold up under millions of requests per day.
- Collaborate across disciplines – work shoulder-to-shoulder with distributed-systems engineers, product designers, and founders to turn complex infrastructure into delightful product.
- Level-up the team – lead design reviews, mentor junior engineers, and introduce best practices for testing, accessibility, and observability.

## What we’re looking for

Must-Have

- 5+ years building production React applications
- Deep knowledge of Tailwind CSS & modern CSS architecture
- Typescript mastery and strong fundamentals in JS/DOM/APIs
- Experience designing REST/JSON or gRPC backends (Node, Go, or similar)
- AuthN/AuthZ design (OIDC, JWT)
- Product sense: you care about UX details & accessibility

Nice-to-Have

- Experience with Tanstack / Next.js
- Data-viz libraries (Recharts, Visx, D3)
- tRPC experience
- Familiarity with GPU or ML tooling dashboards
- Comfort debugging perf issues (Lighthouse, Chrome DevTools)
- Dev-ops chops: CI/CD, Docker, Terraform

You don’t need to tick every “nice-to-have” box—curiosity and the ability to learn quickly matter more.

## Compensation

- Base salary: $120,000 – $180,000
- Equity: significant early-stage grant
- Benefits: full medical/dental/vision, 401(k) with match, generous PTO, commuter + hardware stipends, daily office lunch

## How we work

We iterate fast, test in prod (safely!), and celebrate small wins. You’ll demo work twice a week, pair with systems engineers, and ship to users continuously. Most of us are in the office 3–4 days a week; remote candidates considered if time-zone compatible with Pacific hours.

## Equal Opportunity

[Inference.net](http://Inference.net) is an equal opportunity employer. We value diversity and do not discriminate on the basis of race, color, religion, gender identity, sexual orientation, national origin, veteran status, disability, age, or any other protected status.

Ready to build the front door to planet-scale AI? Send a short note and a link to something you’ve shipped (code, demo, or Dribbble shots) to jobs@inference.net. We can’t wait to chat!

## About Inference

## Company Overview
- **One-liner**: Inference.net provides a marketplace and infrastructure for AI-native teams to deploy, observe, evaluate, and train custom LLMs at dramatically reduced costs by utilizing otherwise wasted GPU capacity from data centers.
- **Entity Type**: Private (Seed stage)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2023
- **Founders**: Amarjot Singh (Co-Founder), Ibrahim Ahmed (Co-Founder, CTO)

## Core Business
- **Primary Industry**: AI Inference Infrastructure / Software Development
- **Target Customers**: B2B; AI-native companies, startups, and enterprises spending over $50k/month on closed-source AI providers; digital banks; decentralized networks; and high-volume AI applications.
- **Mission/Purpose**: "We believe efficient markets for AI inference will drive the widespread proliferation of artificial intelligence over the next decades, leading to unprecedented human flourishing on Earth and beyond. We aim to accelerate this process."

## Products & Services
- **Inference.net API**: A pay-as-you-go, OpenAI-compatible API for serving open-source, custom, and fine-tuned LLMs. Offers 50-90% discounts compared to providers like OpenAI and Anthropic by aggregating spot compute from underutilized data center GPU capacity.
- **Catalyst Deploy**: A deployment platform for hosting LLMs at massive scale across public cloud, private cloud, or hybrid environments, with a claimed 99.99% uptime.
- **Catalyst Observe**: An LLM observability tool that traces every request path (prompts, tool calls, responses, downstream providers) and monitors latency, reliability, usage patterns, and quality signals.
- **Catalyst Evaluate**: A model evaluation system that scores quality across any model or metric, using production traces to validate new model variants against baseline behavior before deployment.
- **Catalyst Train**: Automatic fine-tuning workflows that turn production traces into training datasets. Allows users to train custom frontier-level language models fine-tuned to specific quality, cost, and latency targets in minutes.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed.
- **Total Funding**: $11.8M (Series Seed, announced October 14, 2025).
- **Notable Investors**: Led by Multicoin Capital and a16z CSX, with participation from Topology Ventures, Founders, Inc., and a group of angel investors.
- **Growth Signals**: 100% headcount growth year-over-year (from 5 to 10 employees). LinkedIn follower growth of +173.6% year-over-year. Has deployed custom models for "some of the fastest-growing AI-native companies in the world," including a digital bank with 120M+ customers and a nutrition tracking app that scaled to 10M+ users.

## Competitive Advantages
- **Unique Business Model**: Acts as a spot market for perishable GPU compute, purchasing underutilized data center capacity in small chunks. This creates an inherent cost advantage, passing 50-90% savings to customers.
- **Custom Model Economics**: Their approach trains models up to 100x smaller than GPT-5-class systems that match or exceed frontier model performance for specific tasks, running 2-3x faster and costing up to 90% less.
- **Differentiation Focus**: Pitching against "renting intelligence" from closed providers, arguing that custom models trained on proprietary data become a moat competitors cannot replicate.
- **SOC 2 Type II Compliant**: Full compliance and operational oversight, enabling enterprise adoption.

## Strategic Focus
- **Expand R&D**: Using seed funding to push the frontiers of model and infrastructure performance.
- **Scale Customer Acquisition**: Targeting companies spending over $50k/month on closed-source AI, offering to cut costs and improve performance within 4 weeks.
- **Continuous Improvement Loops**: Building systems that retrain models on fresh production data as use cases evolve, creating "models that get better every cycle."
- **Multi-Model Platform**: Supporting integration with both provider-hosted models (OpenAI, Anthropic, Gemini) and open-source models on optimized infrastructure.

## Why Work Here
- **High-Impact Role in AI Infrastructure**: Working at the intersection of cutting-edge LLM research and practical infrastructure engineering, directly enabling the economics of AI for other companies.
- **Tiny, High-Caliber Team**: Only 10 employees, plus 4 active job openings, suggesting a lean, high-autonomy culture where individuals have outsized impact.
- **Strong Backing**: Backed by top-tier investors including Multicoin Capital and a16z, providing stability and resources despite being an early-stage company.
- **Office Policy**: On-site / In-Office in San Francisco, CA (HQ in SoMa area). Employees work from a physical office, with typical time on-site being "None" (indicating potential flexibility).
- **Culture Signals**: Described as mission-driven ("human flourishing on Earth and beyond"), with a focus on technical excellence and economic efficiency. The company openly shares its philosophy and strategy in blog posts.
- **Active Roles**: Looking for Machine Learning Researchers, Fullstack Engineers (Frontend Focus), Senior Software Engineers (Model Performance), and Applied Machine Learning Engineers – all of which touch core product and research.

## Sources
1. [Inference.net Website](https://inference.net/)
2. [Inference.net Company Page](https://inference.net/company/)
3. [LinkedIn Page](https://www.linkedin.com/company/inference-net)
4. [Built In Profile](https://builtin.com/company/inferencenet)
5. [Seed Round Announcement](https://inference.net/blog/seed-round/)

## Other roles at Inference

- [Senior Software Engineer - Model Performance](https://feeny.ai/job/senior-software-engineer-model-performance-inference-san-francisco-ey1dbf876pf7) — San Francisco, CA
- [Machine Learning Researcher](https://feeny.ai/job/machine-learning-researcher-inference-san-francisco-hm492bpfacsw) — San Francisco, CA
- [Applied Machine Learning Engineer](https://feeny.ai/job/applied-machine-learning-engineer-inference-san-francisco-epe003kkzf34) — San Francisco, CA
- [Filmmaker / Storyteller](https://feeny.ai/job/filmmaker-storyteller-inference-san-francisco-ydsw1y7frf1a) — San Francisco, CA