Research Intern, Efficient Deep Learning

🔥 17 hours ago

🏄 California – Remote

🏄 California – Remote

💵 $38 - $94 / hour

⏰ Full Time

⚪️ Entry-level

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👻 Ghost score 1%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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NVIDIA

WebsiteLinkedInAll Job Openings

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

• Research, design, and implement novel methods for efficient deep learning in diffusion LLMs and multimodal models • Research efficient agentic AI with hybrid inference orchestration across cloud and edge • Work on sampling efficiency, adaptive unmasking, self-speculation / parallel decoding, training and distillation pipelines, and multimodal generation • Develop routing and scheduling policies, on-device versus cloud expert delegation, and resource-aware agent loops • Publish original research • Collaborate with team members and teams • Work with product groups to transfer technology • Collaborate with external researchers

🎯 Requirements

• Pursuing a Ph.D. in Computer Science/Engineering, Electrical Engineering, etc. • Excellent knowledge of theory and practice of machine learning and deep learning • Experience with large language models, diffusion language models, multimodal / vision-language models, or agentic systems is required • Hands-on experience with large-scale model training including data preparation and model parallelization (tensor and pipeline) is required • Outstanding research track record with at least one top-tier conference (ICML, ICLR, NeurIPS, CVPR, ICCV, etc.) • Excellent communication skills • Parallel programming (e.g., CUDA) • Interest or experience in hybrid cloud–edge inference, orchestration, or adaptive routing • Background in pruning, quantization, NAS, or efficient backbones

🏖️ Benefits

• Competitive salaries • Generous benefits package • Intern benefits