Founding Engineer - Applied AI

Founding Engineer - Applied AI San Francisco, CA (Full-time)- In-Office $180k-$230k base annually NO C2C About the Role Hiring a world-class Applied AI Engineer to build the core systems behind their automation engine for hardware engineering. This is a deeply technical, high-impact role. You will be among the first technical hires and will own mission-critical systems end-to-end. The problems are ambiguous, the constraints are real, and the expectations are high. If you move fast from idea to production, care deeply about customer experience, and want to build foundational AI infrastructure for the world's most impactful industries, this role is for you. Key Responsibilities Design and implement core workflows and infrastructure for hardware engineering agents, including intelligent context management, novel indexing approaches, and post-training Build agents and ML models that can interpret, reason over, and manipulate complex engineering design data, integrating with enterprise-grade engineering tools and systems Work closely with customers and the engineering team to deliver AI-powered workflows that are reliable, intuitive, and trusted in production environments Prototype rapidly, validate ideas with real users, and ship frequently Influence engineering culture, architecture decisions, and the future of the product Requirements Must-Have Bachelor's or higher in Computer Science, Machine Learning, or equivalent experience Strong familiarity with LLM architectures and agent research trends Excellent programming skills with experience using ML libraries such as PyTorch, Hugging Face, and W&B Experience building production ML or AI systems Solid practical experience with search and information retrieval Moves fast from idea to production, with a genuine care for customer experience Based in or willing to relocate to San Francisco, or an exceptional remote candidate Nice-to-Have 3+ years in applied machine learning, backend engineering, or AI infrastructure Experience working with machine learning over geometric data, including CAD Track record of high-impact contributions or published papers at top-tier AI labs or teams