Staff/Principal AI Transformation Engineer

Responsibilities

• Lead evaluation, selection, and integration of frontier LLM ecosystems and commercial AI platforms.
• Architect a unified distributed AI platform for data processing, model training, inference pipelines, and evaluation frameworks.
• Embed with autonomous-driving engineering teams to identify bottlenecks and deliver production-ready AI infrastructure, copilots, and developer ecosystems.
• Design scalable LLMOps/MLOps automation for deployment, monitoring, and continuous feedback.
• Optimize GPU cluster utilization, inference latency, throughput, and large-scale production environments.
• Define the technical roadmap for AI infrastructure and connect external innovations with internal systems.
• Write core code, debug deep system issues, and optimize low-level execution paths.
• Influence Algorithms, Infrastructure, and Hardware teams toward adoption of an AI-first engineering paradigm.

Requirements

• Hands-on proficiency in core languages such as C++, Python, Java, and JavaScript.
• Proven experience designing complex system-level architectures while executing hands-on engineering work.
• Experience leading or substantially contributing to large-scale enterprise AI transformation or building enterprise-grade AI/ML platforms from 0 to 1.
• Deep practical experience with distributed LLM training, inference optimization, and large-scale compute cluster infrastructure and operations.
• Hands-on deployment, tuning, and optimization experience with PyTorch, Ray, vLLM, Triton Inference Server, Kubernetes, DeepSpeed, and Megatron-LM.
• Demonstrated ability to align and influence diverse engineering teams without relying on formal administrative authority.
• Preferred: 8–10+ years of engineering experience in systems software, core cloud infrastructure, or production-grade machine learning platforms.
• Preferred: familiarity with autonomous-driving algorithms, robotics, physics-based simulation engines, or ultra-large-scale ML clusters.
• Preferred: experience building AI copilots, autonomous multi-agent frameworks, or developer productivity platforms.
• Preferred: success delivering complex projects in high-pressure or mission-critical environments.
• Preferred: contributions as an open-source maintainer, technical author, or industry conference speaker.

Benefits

• Full-time position with bonus, equity, and benefits in addition to base salary.
• Annual base salary range of $255,000–$351,000, with actual pay determined by location, skills, experience, and education or training.