Director, Engineering – Software Engineering and AI Inferencing Platforms
Vietnam, Hanoi, Vietnam, Ho Chi Minh CityPosted Nov 5, 2025
Overview
- Added in 30 days
- 647
- At this company, still open
Skills named in this posting
- Python
- CUDA
NVIDIA is widely recognized as one of the world’s most desirable employers, leading groundbreaking innovation in Artificial Intelligence (AI), High-Performance Computing (HPC), and Visualization. Our technologies, including the GPU, have transformed industries—from AI Inferencing and AI factory Optimization, and design to data science. Due to continued growth, NVIDIA Vietnam R&D Center (VRDC) is expanding its engineering leadership to accelerate our AI data and factory platform initiatives.
What You’ll Be Doing:
• Build, lead and scale world-class engineering teams in Vietnam, 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’s 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 flagship NVIDIA services.
• Engage with open-source and enterprise data and workflow ecosystems (e.g., Temporal, Gitlab DevOps Platform, RAPIDS, NeMo Curator, Morpheus) to advance accelerated AI factory, data science and data engineering workloads.
• Champion continuous integration, continuous delivery, and engineering best practices across multi-site R&D 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.
What We Need to See:
• Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, or related field.
• 15+ overall years of software engineering experience with 6+ years in senior leadership roles.
• Proven record of managing large, high-performing software teams and delivering complex AI/ML or data-driven products.
• Expertise in cloud, data, and accelerated computing technologies (e.g., Spark, Kubernetes, Dask, Python ecosystem, CUDA).
• Experience collaborating with open-source communities and enterprise partners.
• Strong leadership, communication, and cross-functional coordination skills.
• Strategic mindset with hands-on technical depth in AI, system software, or large-scale data platforms.
Ways to Stand Out from the Crowd:
• Experience building and scaling AI/ML Inferencing platforms from concept to production.
• Background in GPU programming, CUDA optimization, or system performance engineering.
• Deep understanding of microservices, distributed systems, and high-performance data architectures.
• Contributions to open-source projects or developer ecosystems.
• Knowledge of deep learning, RAG, embeddings, or modern text search frameworks.
At NVIDIA, you’ll join a team of world-class innovators shaping the future of computing. Our Vietnam R&D Center is a key part of NVIDIA’s global AI and Software Engineering ecosystem—collaborating across continents to deliver groundbreaking products that redefine what’s possible. If you’re a creative, driven engineering leader passionate about building technology that changes the world, we’d love to hear from you.
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Original posting: jobs.nvidia.com
RISC-V ecosystem
NVIDIA Corporation in the RISC-V ecosystem
RISC-V International: Premier Board
Founded in 1993, NVIDIA is an AI computing company. The company is headquartered in Santa Clara, California.
- NVIDIA is bringing CUDA platform support to RISC-V, i.e. allowing a RISC-V CPU to host CUDA GPU applications
- Publicly credited the RVA23 profile as the enabler: "We wouldn't have considered porting CUDA to RISC-V without it"
- Active in RISC-V International profile/standards work and a frequent presence in RISC-V ecosystem coverage
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