Staff/Principal AI Transformation Engineer
Core
Architect and lead the integration of frontier LLM ecosystems and commercial AI platforms to build a unified distributed AI platform for data processing, model training, inference, and evaluation.
Role type
Staff/Principal AI Transformation Engineer (Systems & Infrastructure)
Builds
Production-ready AI infrastructure, copilots, developer ecosystems, and scalable LLMOps/MLOps automation.
Domain
Autonomous driving, large-scale distributed AI/ML, cloud infrastructure
Deliverable
production ML models | infrastructure | product features
Required skills
C++, Python, Java, JavaScript, distributed LLM training, inference optimization, large-scale compute cluster operations, PyTorch, Ray, vLLM, Triton Inference Server, Kubernetes, DeepSpeed, Megatron-LM, system-level architecture design, hands-on code debugging and low-level execution optimization, technical roadmap definition, cross-functional influence without administrative authority
Preferred skills
autonomous-driving algorithms, robotics, physics-based simulation engines, ultra-large-scale ML clusters, AI copilots, autonomous multi-agent frameworks, developer productivity platforms, high-pressure mission-critical project delivery, open-source maintenance, technical authorship, industry conference speaking
Technologies
PyTorch, Ray, vLLM, Triton Inference Server, Kubernetes, DeepSpeed, Megatron-LM
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; 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
Seniority
Staff/Principal, hands-on IC with strategic influence
