Senior Solutions Architect – Large Scale AI Training

Job not on LinkedIn

🔥 12 hours ago

🌐 Poland, France, +3 more countries – Remote

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💵 zł292.5k - zł507k / year

⏰ Full Time

🟠 Senior

💻 Solutions Engineer

👻 Ghost score 1%

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Logo of NVIDIA

NVIDIA

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Build and manage strategic technical relationships with leading EMEA AI model builders developing large-scale foundation models • Define software stacks and infrastructure for large-scale training and post-training workflows, including Reinforcement Learning • Guide customers on distributed training strategies and efficient large-scale training and post-training recipes using PyTorch, Megatron-LM, or NeMo (RL/Gym) • Help customers optimize training and fine-tuning efficiency at scale, including GPU utilization, communication overlap, and memory management • Collaborate with NVIDIA product and research teams to present customer needs • Craft NVIDIA product roadmap based on customer feedback • Build or support hackathons, demos, and technical conferences to animate the developer community

🎯 Requirements

• MS or PhD in Computer Science, Engineering, or equivalent experience • Over 7 years of practical experience in distributed AI training • Direct involvement with HPC and/or AI environments with multi-node GPU clusters • Solid understanding of training infrastructure and its effects on efficiency and scalability • Strong proficiency with Megatron-LM, NeMo, or equivalent distributed training frameworks • Excellent communication skills with ability to engage research scientists and infrastructure engineers • Experience in fine-tuning with Reinforcement Learning (RLVR, RLHF) at scale • Experience with LatentMoE, expert load balancing, and speculative decoding for MoE inference • Prior experience in an AI Datacenter/HPC center, national lab, or frontier AI lab environment • Published work or open-source contributions in distributed training

🏖️ Benefits

• Highly competitive salaries • Comprehensive benefits package • Equal opportunity employer

Apply Now

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