Stealth Industrial AI Startup

San Francisco HQ | Onsite | Visa Sponsorship OK | Equity + Cash

Who We Are

We’re a stealth-mode startup solving the multi-trillion dollar equipment failure problem plaguing more than 25% of U.S. GDP across manufacturing, mining, energy, and oil & gas. Backed by $2 million in pre-seed funding and currently serving multiple enterprise customers, we’re building an AI-powered platform that automates critical knowledge workflows and augments physical-world tasks to allow any organization to keep their equipment running at full capacity. Our focus is to not simply to deliver software, but tangible impact, resulting in a better quality of life for our users and operational excellence across production environments.

The Role:

• Architect and build the foundational AI/ML engine powering our agentic maintenance workflows — from predictive insights to knowledge-augmented copilots.
• Own core LLM/RAG pipelines, contextual engineering systems, and agent orchestration layers that drive real-time, multi-modal interactions.
• Partner with the full-stack team to tightly integrate AI into user-facing features with end-to-end performance observability.
• Design and tune models for noisy, physical-world data — from predictive maintenance algorithms to retrieval and context management systems grounded in tribal knowledge.
• Develop MCP (Model Context Protocol) servers and integrations for multi-source data querying.
• Collaborate with frontline operators and plant-floor engineers to validate AI output and performance in production environments.
• Establish our MLOps stack from day one — versioning, A/B testing, rollback, and monitoring — across a modern AWS-native infra.
• Work side-by-side with the founders to set product strategy, define roadmap, and scale real-world AI usage.

What We Require:

• 3–5 years of total experience, including 1–2 years focused on ML/AI systems.