Founding Engineer, ML + Full-Stack

Founding Engineer, ML + Full-Stack Onsite (San Francisco, CA) Full-time View all jobs Mission Raise humanity’s starting point with every act of work. Humanity should not keep paying the cost of knowledge it has already created. Autostep measures outcomes from human and AI work, identifies what companies should change, and helps make that change happen. We have real customer pull. We’re hiring two founding engineers to help turn that pull into exceptional, repeatable customer results.

You’ll work across machine learning, full-stack product, forward deployment, and desktop systems. This will be hard. You’ll work directly with mid-market and enterprise customers, ship constantly, and deal with requirements that are messy, incomplete, and sometimes wrong. Your job is to put structure around that ambiguity, figure out what should actually be built, and ship it. What you’ll do - Build and improve our data + ML pipeline across accuracy, context, speed, evals, algorithms, agents, and cost. - Ship new projects, product surfaces, UI, experiments, and features constantly.

Small projects and improvements should be able to ship daily. - Improve our existing Mac/Windows desktop app across reliability, performance, deployment, and new capabilities. - Work directly with customers to clarify messy requirements and environments, question assumptions, define the actual problem, and create as much value as possible. - Turn lessons from individual customers into repeatable product improvements that make the next deployment better. - Keep engineering clean as you move quickly: requirements, PRDs, Linear, documentation, tests, decisions, and deadlines should stay current. - Use AI coding aggressively.

We do not care whether you use one agent or twenty. We care whether you understand what shipped and whether it works. What we’re looking for You have driven real outcomes through things you’ve built or shipped and can show us what changed because of your work. Strong Python matters. Our current world includes Python, Jupyter notebooks, TypeScript, React/Next.js, AWS, Supabase/Postgres, Electron, Rust, Vercel, GitHub, and modern AI coding tools.

We care about applied ML, algorithms, evals, agents, LLMs, data systems, systems design, desktop software, UI/product taste, and enterprise infrastructure. You do not need every skill today. You need to learn unusually fast. You can talk to customers, explain technical systems clearly, test assumptions, and question bad ones. When something goes wrong, you investigate, communicate clearly, and find a path forward.

Degrees are optional. Shipped work matters more. What you get - $100K in LLM/model/compute credits to help improve the product. Create great customer outcomes with it and we’ll expand the budget. - Additional model, developer, and startup benefits we’ll show you. - Occasional access to invite-only founder/startup events. - Surfing when time and conditions permit. - A chance to learn deeply across applied ML, AI systems, product, enterprise infrastructure, and some genuinely unusual technical problems. - Work directly with the founder at a company backed by YC and Neo . - Work alongside investors who advise us, including Walden Yan (Co-Founder, Cognition, $26B), Erik Goldman (Co-Founder, Vanta, $4B), Charles Mourani (Co-Founder, Cherry, $2B), Kabir Barday (Co-Founder, OneTrust, $4.5B), and Kunal Shah (CEO of WhatsApp; Co-Founder, CRED, $4.5B), alongside other reputable enterprise founders and co-founders.

Success looks like Customers get better outcomes because of what you shipped. They use it. They get exceptional results. They renew and expand. Deployments and product quality improve. What you learn from one deployment makes the next deployment faster and better. This is a high-ownership role from day one. We expect high ownership, speed, and measurable outcomes. Skills Python · Machine Learning · Large Language Models · AI Agents · Evals · AWS · TypeScript · React · Electron · Rust · Jupyter · Software Architecture · Software Security · Windows · macOS About the interview Phone Screen References In-Person Technical Interview(s) in San Francisco Preferable / Remote Interview - AI-Native Technical Build - Customer and Forward-Deployment Simulation Final Conversation Apply Autofill from resume Drag & drop or upload to autofill your application.

Upload file First Name \* ​ Last Name \* ​ Email \* ​ LinkedIn Profile URL \* ​ Phone Number \* ​ Show us a video of something you built that you are most proud of. Submissions without a link to a YouTube/Loom video that walks through your project and what it does will not be accepted. \* ​ What is your current AI coding stack, and one workflow or trick most engineers do not use? \* ​ Optional: Share a link to a recent coding session or build log that shows how you work.

Only share material you are allowed to share. Not sharing one will not affect your application. ​ Are you legally authorized to work in the US? \* YesNo Will you now or in the future require visa sponsorship to work in the US? \* YesNo Resume \* Drag and drop file or browse computer (PDF or DOCX, 5 MB maximum) Checking your Browser… Verify you are human Verifying... Stuck? Troubleshoot Success! Verification failed Troubleshoot Verification expired Refresh Verification expired Refresh Troubleshoot Cloudflare, opens in a new tab Privacy • Help Apply Jobs powered by \\ \\ By applying you agree to Dover's terms.