NVIDIA

Full-stack Engineer

• Collaborate on the design and development of the Dynamo Kubernetes stack
• Introduce new features to the Dynamo Python SDK and Dynamo Rust Runtime Core Library
• Design, implement, and optimize distributed inference components in Rust and Python
• Contribute to the development of disaggregated serving for Dynamo-supported inference engines (vLLM, SGLang, TRT-LLM, llama.cpp, mistral.rs)
• Improve intelligent routing and KV-cache management subsystems
• Contribute to open-source repositories, participate in code reviews, and assist with issue triage on GitHub
• Work closely with the community to address issues, capture feedback, and evolve the framework’s APIs and architecture
• Write clear documentation and contribute to user and developer guides.

Principal Software Engineer – Dynamo

• Build microservices that are reliable, scalable, and maintainable.
• Improve the current system's ability to schedule and utilize resources, improve performance, increase reliability, and provide better throughput.
• Design interfaces that are efficient and easy to use for hundreds of engineers throughout the world.
• Join an agile and dynamic software development team with very high production quality standards.
• Participate in the full life-cycle of tool development, test, and deployment.
• Work closely with other team members and internal customers to understand their processes, requirements, and needs.
• Directly contribute to the overall quality of and improve time to market for NVIDIA's next-generation chips.

EDA System Software Engineer

Artificial Intelligence

• Conduct weekly face-to-face training sessions for NVIDIA’s customers and partners, with travel up to 80% as needed
• Partner with NVIDIA’s sales, partner, product, and technical marketing teams to ensure partner sellers can confidently position, recommend and implement NVIDIA AI solutions
• Develop and refine sales training materials focused on NVIDIA AI and data center technologies and sales motions
• Collaborate with SMEs to design courses aligned with company strategy
• Listen actively to partner feedback during workshops, translating insights into actionable improvements for future sessions
• Recruit and train internal team members to deliver specific workshop modules
• Create delivery notes, certification criteria, and assessment materials that ensure consistent quality across sessions

Senior AI Sales Training Specialist

Solutions Engineer

• Be part of our EMEA Retail Solution Architecture Team driving NVIDIA technology adoption at key Retail & CPG customers
• Secure design wins in both Data Center, Edge and Cloud Deployments
• Become a trusted technical advisor with our customers
• Work on exciting projects and deploy AI solutions in production using Data Processing for Retail
• Lead customer proof-of-concepts (PoCs) of next-gen platforms for deploying Retail Industry solutions to key use-cases like forecasting, logistics, and customer recommendation and personalization, real-time and at scale
• Collaborate with NVIDIA Engineering, Product, Sales teams on innovative AI optimization techniques
• Drive adoption of NVIDIA's Accelerated Compute Platforms with focus on growing our customer's Software, DevOps and MLOps capabilities

Solution Architect, Data Science – Retail

• Guide customers through the end-to-end process of AI adoption
• Collaborate with business/account team to identify technical needs and goals
• Enable customer adoption of NVIDIA technology
• Keep up to date on AI advancements in the domain
• Document knowledge and teach others

Solution Architect – Computational Chemistry, Material Science

Engineer

• Lead ME Mass production Adapters and Switches infrastructure capabilities at our Vietnam contract manufacture site.
• Find opportunities for potential processes improvements and collaborate with multi-functional teams to implement.
• Assure CEM capacity and production capabilities always in place to support NVIDIA RBP requirements.
• Work concurrently with NVIDIA engineering teams, CEMs, and fixtures suppliers to improve Infrastructure fixtures and test stations.
• Represent mass production ME Infrastructure requirements at Vietnam CEM.

Senior Mass Production Infrastructure Engineer

Application Engineer

• Be a technical specialist on GPU and networking products, directly supporting sales account managers to secure build wins
• Actively establish and nurture technical relationships with engineers, management, and architects at key customer accounts
• Identify customer architectures and key product requirements in the CSP/ODM AI market to successfully implement NVIDIA's solutions
• Provide onsite support to solve hardware and software problems, with a focus on deep learning training and inference
• Lead the product through its entire lifecycle, from the design-in phase to end-of-life, ensuring flawless execution and customer happiness
• Develop technical solutions including hardware & software demos and example system builds
• Offer technical and sales training to direct sales teams and channel partners
• Establish strong communication channels and collaborative relationships with internal teams to ensure a positive customer experience

Senior Field Application Engineer

• Lead and mentor a mixed team of SW engineers and researchers, balancing the agility of research with the responsibility of production software engineering.
• Partner with internal engineering teams (Hardware, Architecture, Research) to analyze their workflows, identify friction points, and architect Agentic AI solutions to accelerate their work.
• Actively monitor the latest AI trends, academic papers, and technical blogs (LLMs, Agents, RAG).
• Translate these insights into concrete features and tools for the team.
• Design scalable frameworks for AI agent interaction, ensuring they can reason, plan, and orchestrate tasks within complex engineering environments.
• Define and implement the software lifecycle for AI models - from fine-tuning to deployment - utilizing NVIDIA’s AI deployment tools and ensuring seamless CI/CD.
• Ensure reliable operation of agent fleets, optimizing for latency and resource consumption while maintaining security and access controls.

Manager, AI Agents – Applied Research

• Responsible for platform software related to GPU systems
• Partnering with hardware, silicon, driver, and data center/Cloud units
• Launch new GPU platforms and resolve complex system challenges
• Engage in code reviews and contribute to production codebases
• Develop knowledge of OS and system software focusing on Linux internals

Senior Software Engineer – GPU Platforms

Operations

• Lead and refine comprehensive business processes supporting enterprise customer training, public workshops, conference training labs, and various training programs
• Own end-to-end coordination and execution of workshops and conference training events, including scheduling, instructor assignments, registration, and logistics
• Lead the successful delivery of workforce training plans
• Manage vendor and partner workflows to plan and deliver workshops at scale
• Handle customer support inquiries for training programs and ensure high-quality responses
• Contribute to cross-functional initiatives to improve systems and automate workflows

Training Operations Manager, Deep Learning Institute

Architect

• Architect Performance Tooling: Develop infrastructure tools/libraries for GPU performance analysis, visualization, and automated workflows used across GPU SW/HW development life cycle
• Unlock Architectural Insights: Analyze GPU workloads to identify bottlenecks and define new hardware profiling features that enhance perf debug and profiling capabilities
• AI-Powered Automation: Build AI/ML-driven tools to automate performance analysis, generate perf optimization guidance, and improve user experience of profiling infrastructure
• Cross-Stack Collaboration: Partner with kernel developers, system software teams, and hardware architects to support performance study, improve CUDA software stack, and co-design performance-centric solutions for current and next-generation GPU architecture