Founding Engineer - Applied AI

About the job Founding Engineer - Applied AI Founding Engineer - Applied AI Company: Antes Location: San Francisco, CA (in person highly preferred; exceptional remote candidates considered) Compensation: $180,000 - $250,000 + equity Employment Type: Full-time About Antes Antes is a stealth startup building AI for complex hardware manufacturers, at the intersection of AI, hardware development and policy. It partners with iconic automotive, aerospace and industrial manufacturers and is backed by General Catalyst, Kleiner Perkins and the parent company of Ferrari. The founding team spans AI, advanced engineering and policy, including a former America's Cup world champion, Stanford AI Lab researchers, a former president of Hyundai, a CTO of Caterpillar, and a former Chairman of the FAA and FCC. The Role Antes is hiring an Applied AI Engineer to build the core systems behind its automation engine for hardware engineering. You will design, implement and post-train AI agents that power critical product development workflows for global enterprise customers, retrieving, interpreting and manipulating complex engineering design data inside real engineering environments. As one of the first technical hires, you will own mission-critical systems end to end. What You Will Do Design core workflows and infrastructure for hardware engineering agents: context management, novel indexing and post-training. Build agents and ML models that reason over and manipulate complex engineering design data, integrated with enterprise engineering tools. Work with customers and the team to deliver reliable, trusted AI workflows in production. Prototype rapidly, validate with real users and ship frequently. Shape engineering culture, architecture and the product's future. What You Bring Bachelor's or higher in Computer Science, Machine Learning or equivalent experience Strong familiarity with LLM architectures and agent research Excellent programming skills with ML libraries such as PyTorch, Hugging Face and Weights & Biases Experience building production ML or AI systems Transparent Search Group