Engineering Manager, Deep Learning Inference

🔥 1 hour ago

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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

• Lead, mentor, and scale a high-performing engineering team focused on deep learning inference and GPU-accelerated software • Guide the strategy, roadmap, and execution of NVIDIA's OSS inference frameworks engineering • Partner with internal compiler, libraries, and research teams to deliver end-to-end optimized inference pipelines across NVIDIA accelerators • Oversee performance tuning, profiling, and optimization of large-scale models for LLM, multimodal, and generative AI applications • Guide engineers in adopting best practices for CUDA, Triton, CUTLASS, and multi-GPU communications (NIXL, NCCL, NVSHMEM) • Represent the team in roadmap and planning discussions, ensuring alignment with NVIDIA’s broader AI and software strategies • Foster a culture of technical excellence, open collaboration, and continuous innovation

🎯 Requirements

• MS, PhD, or equivalent experience in Computer Science, Electrical/Computer Engineering, or a related field • 6+ overall years of software development experience, including 3+ years in technical leadership or engineering management • Strong background in C/C++ software design and development; proficiency in Python is a plus • Hands-on experience with GPU programming (CUDA, Triton, CUTLASS) and performance optimization • Proven record of deploying or optimizing deep learning models in production environments • Experience leading teams using Agile or collaborative software development practices

🏖️ Benefits

• highly competitive salaries • comprehensive benefits package

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