Design and build production-ready AI agents and infrastructure for hardware engineering workflows. Implement context management, indexing, and post-training; interpret and manipulate complex engineering design data; integrate with enterprise tools; collaborate with customers; prototype and ship solutions; influence architecture and engineering culture.
About the Role
What You’ll Do
We’re looking for a world-class Applied AI Engineer to build the core systems behind our automation engine for hardware engineering. In this role, you’ll design, implement and post-train AI agents that power critical product development workflows for global enterprise customers. You’ll work on novel AI systems that retrieve, interpret, and manipulate complex engineering design data, integrating deeply into real-world engineering environments.
This is a deeply technical, high-impact role. You’ll be among the first technical hires, and will own mission-critical systems end to end. 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.
- Engineering Agent Workflows
- Design and implement core workflows and infrastructure for hardware engineering agents, including intelligent context management, novel indexing approaches and post training.
- Design Data Interpretation
- Build agents and ML models that can interpret, reason over, and manipulate complex engineering design data, integrating with enterprise-grade engineering tools and systems.
- Direct Customer Collaboration
- Work closely with customers and the engineering team to deliver AI-powered workflows that are reliable, intuitive, and trusted in production environments.
- Move Fast, Learn Fast: Prototype rapidly, validate ideas with real users, and ship frequently.
- Help Shape the Company: Influence engineering culture, architecture decisions, and the future of the product.
Required Qualifications
- Bachelor's or higher in Computer Science, Machine Learning, or equivalent experience
- Strong familiarity with LLM architectures and agent research trends
- Excellent programming skills and experience with ML libraries (e.g., PyTorch, Hugging Face, W&B)
- Experience building production ML or AI systems
- Solid practical experience with search and information retrieval
Preferred Qualifications
- 2+ years of experience in applied machine learning, backend engineering or AI infrastructure
- Experience working with machine learning over geometric data
- Track record of high-impact contributions or papers
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