Latest ML Engineering jobs at Luma AI

Build and scale distributed reinforcement learning infrastructure for post-training large multimodal foundation models, including rollout generation, environments, rewards, and evaluation systems for agentic tasks.

Tech Lead Manager to hands-on lead the inference platform team at Luma AI. Own the full serving stack for multimodal models across thousands of GPUs, spending 50%+ time as IC on architecture, optimization, and debugging while growing the team and setting technical direction.

Builds and trains large-scale multimodal agentic models involving reasoning, planning, coding, and tool calling. Requires strong ML foundations, PyTorch expertise, and experience with distributed training on massive datasets.

Develops and optimizes inference engines for multimodal AI models, integrating new architectures, building scheduling systems, and managing large-scale GPU deployments. Requires strong Python, model serving frameworks like PyTorch/vLLM, and Kubernetes expertise.

Builds foundational ML platform infrastructure including model serving pipelines, GPU scheduling systems, and CI/CD for large-scale multimodal AI models. Requires 5+ years in distributed systems with expertise in Python, Kubernetes, and AWS.

Builds and optimizes distributed training infrastructure for large-scale multimodal AI models across thousands of GPUs. Requires deep expertise in PyTorch, CUDA, parallelization techniques, and GPU clusters.