Found Description
A fantastic opportunity for a Senior MLOps Engineer to join a Global AI/Deep Tech company, complimenting the technical vision of our Training and Inference Optimization team.
In this high-impact role, you will architect the infrastructure that powers our next-generation AI models. You will bridge the gap between systems programming and machine learning, optimizing large-scale LLM training via NVIDIA NeMo and building ultra-high-throughput serving systems using vLLM, TensorRT-LLM, and SGLang.
***Option to also work from Madrid, Zaragoza or San Sebastian***
Key Responsibilities
Training Infrastructure: Architect and maintain scalable distributed training pipelines using NVIDIA NeMo/Nemotron/Megatron-Bridge. You will optimize GPU utilization, manage complex checkpointing strategies, and implement automated fault tolerance for long-running jobs.
Inference Orchestration: Lead the deployment of LLMs using vLLM, TensorRT-LLM, or SGLang. You will implement and tune cut...
In this high-impact role, you will architect the infrastructure that powers our next-generation AI models. You will bridge the gap between systems programming and machine learning, optimizing large-scale LLM training via NVIDIA NeMo and building ultra-high-throughput serving systems using vLLM, TensorRT-LLM, and SGLang.
***Option to also work from Madrid, Zaragoza or San Sebastian***
Key Responsibilities
Training Infrastructure: Architect and maintain scalable distributed training pipelines using NVIDIA NeMo/Nemotron/Megatron-Bridge. You will optimize GPU utilization, manage complex checkpointing strategies, and implement automated fault tolerance for long-running jobs.
Inference Orchestration: Lead the deployment of LLMs using vLLM, TensorRT-LLM, or SGLang. You will implement and tune cut...
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