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NVIDIA

Designs the chips and software that power AI

Director – Engineering - Software Engineering and AI Inferencing Platforms

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • A bachelor's, master's, or PhD in Computer Science, Computer Engineering, or a related field is required.
  • At least 15 years of overall software engineering experience and at least 6 years in senior leadership roles are required.
  • A proven record of managing large, high-performing software teams and delivering complex AI/ML or data-driven products is required.
  • Expertise in cloud, data, and accelerated computing technologies, including Spark, Kubernetes, Dask, the Python ecosystem, and CUDA, is required.
  • Experience collaborating with open-source communities and enterprise partners is required.
  • Strong leadership, communication, and cross-functional coordination skills are required.
  • A strategic mindset with hands-on technical depth in AI, system software, or large-scale data platforms is required.

Responsibilities

  • Build, lead, and scale engineering teams in Vietnam while collaborating with global counterparts across system software, data science, and AI platforms.
  • Drive the design, architecture, and delivery of high-performance system software platforms that power NVIDIA AI products and services.
  • Partner with global teams across machine learning, inference services, and hardware/software integration to ensure performance, reliability, and scalability.
  • Oversee the development and optimization of AI delivery platforms in Vietnam, including NIMs, Blueprints, and other NVIDIA services.
  • Engage with open-source and enterprise data and workflow ecosystems, including Temporal, GitLab DevOps Platform, RAPIDS, NeMo Curator, and Morpheus, to advance accelerated AI factory, data science, and data engineering workloads.
  • Champion continuous integration, continuous delivery, and engineering best practices across multi-site research and development centers.
  • Collaborate with product management and cross-functional stakeholders to ensure enterprise readiness and customer impact.
  • Develop and deploy standard processes for large-scale distributed system testing, encompassing stress, scale, failover, and resiliency testing.
  • Ensure security and compliance testing aligns with industry standards for cloud and data center products.
  • Mentor and develop talent within the organization, fostering a culture of quality and continuous improvement.

Desired Qualifications

  • Experience building and scaling AI/ML inferencing platforms from concept to production.
  • A background in GPU programming, CUDA optimization, or system performance engineering.
  • A deep understanding of microservices, distributed systems, and high-performance data architectures.
  • Contributions to open-source projects or developer ecosystems.
  • Knowledge of deep learning, retrieval-augmented generation (RAG), embeddings, or modern text search frameworks.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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