About the Company

We are a profitable, well-funded company (over $110M raised) building the AI and software backbone for next-generation vehicles—technology already deployed in millions of cars worldwide.

Our platform powers the shift toward software-defined vehicles, enabling intelligence, adaptability, and automation across global OEMs.

If you want to build AI systems that have immediate real-world impact at global scale, this is the place.

About the Role

We’re looking for a Staff AI/ML Engineer to design, build, and deploy advanced AI systems—including LLMs, RAG pipelines, and agentic frameworks—directly into automotive environments.

In this role, you will work closely with our highly technical, hands-on CTO, contributing to architectural decisions that shape the future capabilities of connected, intelligent vehicles. This is not a feature-shipping role—this is category-defining engineering.

What You’ll Do

• Lead the design and development of LLM-based systems, RAG architectures, and agentic AI pipelines for real-world automotive applications.

• Build end-to-end ML systems that ultimately ship into millions of vehicles globally.

• Evaluate and select model architectures, balancing accuracy, latency, cost, safety, and real-time constraints.

• Collaborate directly with the CTO on high-level architecture, research direction, and core technical decisions.

• Partner with data engineering and platform teams to ensure scalable data pipelines, embeddings, vector stores, and inference services.

• Deploy machine learning and LLM workflows into production environments with strict performance, reliability, and safety requirements.

• Contribute to the long-term roadmap of next-gen intelligent vehicle capabilities.

What We’re Looking For

Must-Have Qualifications

• 6+ years as an AI/ML Engineer at an AI-focused or ML-heavy technology company.

• Expert-level Python skills; ability to write clean, modular, production-grade code.

• Deep experience with TensorFlow or PyTorch.

• Hands-on implementation of RAG systems (vector databases, embeddings, chunking, retrieval optimization).

• Experience with agentic frameworks and autonomous LLM pipelines.

• Strong knowledge of data engineering, feature pipelines, and model lifecycle management.

• Experience with cloud-based model deployment (AWS, GCP, Azure) and ML Ops practices.

• Proficiency with ML evaluation frameworks (e.g., Ragas, LLM-as-a-judge, traditional ML metrics).

Why Join Us

• Build AI that goes into real production vehicles—not demos.

• Work directly with a CTO who still writes code and deeply influences engineering.

• Join a company that is profitable, well-capitalized, and in high demand by global OEMs.

• Shape the future architecture of software-defined vehicles.

• High ownership, high impact, and a rare chance to define an emerging category.

Ready to Build the Future of Automotive AI?

If you're excited about architecting AI systems that scale across millions of vehicles worldwide, we’d love to speak with you.