Staff/Principal AI Transformation Engineer

Responsibilities

• Lead evaluation, selection, and integration of frontier LLM ecosystems and commercial AI platforms.
• Own the architecture of a unified distributed AI platform covering data processing, model training, inference pipelines, and evaluation frameworks.
• Embed with autonomous driving engineering teams to identify bottlenecks and deliver production-ready internal AI ecosystems such as AI DevOps and AI Copilots.
• Design and implement resilient automation pipelines for LLM deployment, monitoring, and continuous feedback.
• Optimize GPU cluster utilization, inference latency, throughput, and large-scale production infrastructure.
• Define the technical roadmap for AI infrastructure and connect external AI and systems innovations with internal engineering systems.
• Write core code, debug deep system issues, optimize low-level execution paths, and influence engineering teams toward AI-first development.

Requirements

• Demonstrated ability to design complex system-level architectures while remaining hands-on with core software engineering.
• Proficiency in C++, Python, Java, or JavaScript.
• Experience building technical authority and aligning Algorithms, Infrastructure, and Hardware teams without relying on formal administrative authority.
• Experience leading or substantially contributing to a large-scale corporate AI-native transformation or building enterprise-grade AI/ML platforms from 0 to 1.
• Hands-on deployment, tuning, and optimization experience with PyTorch, Ray, vLLM, Triton Inference Server, Kubernetes, DeepSpeed, and Megatron-LM.
• Deep practical experience in distributed LLM training and inference optimization and large-scale compute cluster infrastructure and operations.
• Preferred: familiarity with autonomous driving algorithms, robotics, physics-based simulation engines, or large-scale ML training and serving clusters.
• Preferred: 8–10+ years of professional engineering experience in systems software, core cloud infrastructure, or production-grade machine learning platforms.
• Preferred: experience building AI Copilot applications, autonomous multi-agent frameworks, or developer productivity platforms.
• Preferred: experience delivering projects in complex, high-pressure, or mission-critical environments.
• Preferred: contributions as an open-source maintainer or owner, technical author, blogger, paper author, or industry conference speaker.

Benefits

• Full-time position with bonus, equity, and benefits in addition to base salary.