Senior Principal AI Engineer (Automotive)

TL;DR

Senior Principal AI Engineer (Distributed Training/GPU): Designing and operating distributed training systems for large neural networks across GPU clusters with an accent on optimizing multi-node execution and throughput. Focus on eliminating networking bottlenecks, improving training stability, and scaling large-model pipelines for automotive AI.

Location: Remote (USA)

Company

Global industry leader in creating unique AI-powered voice assistants and moving experiences for the automotive world, partnering with leading automakers globally.

What you will do

• Design and operate distributed training systems for large neural networks (autoregressive, diffusion, SSM) across GPU clusters.
• Optimize multi-node, multi-GPU execution to maximize throughput and minimize communication overhead.
• Build and optimize GPU cluster orchestration using Slurm, Kubernetes, Ray, and RunAI.
• Debug and optimize distributed communication utilizing NCCL, RDMA, InfiniBand, and NVLink.
• Scale large-model training pipelines using PyTorch Distributed, Megatron-LM, and DeepSpeed.
• Apply advanced memory optimization techniques including activation checkpointing and ZeRO offload strategies.

Requirements

• Deep hands-on experience with distributed systems or ML systems.
• Proven experience running large-scale workloads on GPU clusters.
• Production experience with PyTorch distributed training.
• Strong understanding of data, tensor, and pipeline parallelism strategies.
• Low-level understanding of GPU communication and networking.
• Must be based in the USA.

Culture & Benefits

• Opportunity to build the foundation for large-scale AI in the automotive industry.
• Collaboration with a passionate, dedicated global team.
• Exposure to cutting-edge LLM and foundation model infrastructure.
• Commitment to Equal Employment Opportunity (EEO) and a diverse, compliant workplace.