Research Scientist / Engineer - Training Infrastructure
$187.5k - $395kTryApplyNow
- Research Scientist / Engineer – Training InfrastructureLuma AIFull TimemidCAPosted Yesterday## Role OverviewLuma AI is hiring a mid-level Research Scientist / Engineer – Training Infrastructure. This is a full-time role in CA. posted yesterday. Full responsibilities, required qualifications, and the apply link are listed in the description below.## Resume Keywords to IncludeMake sure these keywords appear in your resume to improve ATS scoringGoLinuxRESTPyTorchPipelineCompensationLumaAISign up free to auto-tailor your resume with all these keywords and get a higher ATS score## Job DescriptionAbout Luma AILuma’s mission is to build multimodal AI to expand human imagination and capabilities. We believe that multimodality is critical for intelligence. To go beyond language models and build more aware, capable and useful systems, the next step function change will come from vision. So, we are working on training and scaling up multimodal foundation models for systems that can see and understand, show and explain, and eventually interact with our world to effect change.### About the RoleThe Training Infrastructure team at Luma is responsible for building and maintaining the distributed systems that enable training of our large-scale multimodal models across thousands of GPUs. This team ensures our researchers can focus on innovation while having access to reliable, efficient, and scalable training infrastructure that pushes the boundaries of what's possible in AI model development. We are looking for engineers with significant experience solving hard problems in PyTorch, CUDA and distributed systems. You will work alongside the rest of the research team to build & train cutting edge foundation models on thousands of GPUs that are built to scale from the ground up.### Responsibilities* Design, implement, and optimize efficient distributed training systems for models with thousands of GPUs* Research and implement advanced parallelization techniques (FSDP, Tensor Parallel, Pipeline Parallel, Expert Parallel)* Build monitoring, visualization, and debugging tools for large-scale training runs* Optimize training stability, convergence, and resource utilization across massive clusters### Experience* Extensive experience with distributed PyTorch training and parallelisms in foundation model training* Deep understanding of GPU clusters, networking, and storage systems* Familiarity with communication libraries (NCCL, MPI) and distributed system optimization* (Preferred) Strong Linux systems administration and scripting capabilities* (Preferred) Experience managing training runs across >100 GPUs* (Preferred) Experience with containerization, orchestration, and cloud infrastructure### CompensationThe base pay range for this role is $187,500 – $395,000 per year.About LumaLuma’s mission is to build unified general intelligence that can generate, understand, and operate in the physical world.We believe that multimodality is critical for intelligence. To go beyond language models and build more aware, capable and useful systems, the next step function change will come from vision. So, we are working on training and scaling up multimodal foundation models for systems that can see and understand, show and explain, and eventually interact with our world to effect change.
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Vacancy posted 3 days ago
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