NVIDIA

Full-stack Engineer

• Design, implement, and debug changes in the NVIDIA SW stack to take next‑generation HW from design/development stage to production, with a focus on kernel‑mode SW.
• Develop and optimize CPU, GPU, and platform‑level power‑management features , including power‑state transitions, DVFS tuning, residency improvements, and system idle/active power optimization.
• Own bring‑up and hardening of power‑related kernel and embedded firmware components, ensuring accurate interactions between SOC subsystems, PMU firmware, regulators, and OS‑level power frameworks.
• Follow devices throughout the development lifecycle into customer desktops, notebooks, workstations, and datacenter systems — ensuring efficient performance‑per‑watt , thermal‑aware scheduling, and system resilience.
• Be heavily involved in emulation, silicon bring‑up, power/perf validation, and product hardening required to build our groundbreaking products.
• Collaborate globally with cross‑functional teams (HW, firmware, OS, platform power teams) to drive end‑to‑end power behavior , telemetry debugging, and optimization across the full system stack.

Senior System Software Engineer – Power Management

Solutions Engineer

• Drive the implementation and deployment of NVIDIA Inference Microservice (NIM) solutions
• Apply NVIDIA NIM Factory Pipeline to package optimized models (including LLM, VLM, Retriever, CV, OCR, etc.) into containers, providing standardized API access for on-prem or cloud deployment
• Refine NIM tools for the community, aiding them in building high-performing NIMs
• Build and implement agentic AI tailored to customer business scenarios using NIMs
• Deliver technical projects, demos, and client support tasks as directed by the Solution Architecture Leadership
• Provide technical support and mentorship to customers, facilitating the adoption and implementation of NVIDIA technologies and products
• Collaborate with multi-functional teams to develop and broaden our AI solutions portfolio
• Be an internal advocate for NVIDIA software and total solutions within the technical community by incorporating NVIDIA technology, especially inference services, into LHA, business partners, and the broader community
• Assist in supporting the NVAIE team and driving NVAIE business in China.

Senior Solution Architect – AI Development

Technical Program Manager

• Define and manage program schedules, deliverables, and key milestones aligned with Cloud Service Providers (CSPs) and their ODM/OEM partners’ roadmaps and requirements.
• Translate CSP and partner requirements into actionable execution plans.
• Provide horizontal leadership across cross‑functional teams.
• Act as the primary customer interface for assigned programs.
• Drive end‑to‑end program execution from design through production deployment.

Enterprise Customer Technical Program Manager

Frontend Engineer

• Design, implement, and maintain installation and packaging workflows for NVIDIA networking software across major Linux distributions (Debian, Ubuntu, RHEL, SLES, etc.).
• Develop and support meta-packages, profiles, and tools to streamline user-space installation and configuration.
• Work with distribution maintainers to ensure compatibility and smooth delivery through native packaging systems (DEB, RPM).
• Perform system-level testing and verification of package installations on various platforms and OS versions.
• Collaborate with cross-functional teams (kernel, QA, release engineering, and support) to ensure installation quality and maintainability.
• Contribute to Linux kernel driver development and backporting to support advanced networking features.

Software Linux Engineer – Installation and Packaging

Project Manager

• Build, mentor, and lead a high-performing distributed team of project and program managers, promoting a culture of accountability and continuous improvement.
• Develop, implement, and govern project management processes, tools, templates, policies, and metrics to ensure consistency and efficiency across all customer and datacenter deployment programs.
• Oversee the entire project portfolio, prioritizing initiatives, managing dependencies, and ensuring alignment with organizational strategy and long-term datacenter deployment roadmaps.
• Ensure all datacenter and customer projects (from inception through design‑in, deployment, commissioning, and post‑production support) adhere to established timelines, scope, budgetary constraints, quality, and safety standards.
• Optimize resource allocation across the portfolio, balancing PMO and cross‑functional capacity against strategic priorities and customer commitments.
• Work closely with internal and external matrixed teams—including contractors and systems integrators—that support datacenter deployment and lifecycle operations.
• Serve as the primary interface for executives, customers, partners, and vendors, coordinating cross‑functional teams to resolve issues quickly and ensuring third‑party SOWs and deliverables provide high‑quality, cost‑efficient support for NVIDIA datacenter and cloud deployments.
• Proactively identify project and portfolio-level risks, develop mitigation strategies, and implement quality assurance processes to minimize disruptions and ensure compliance with regulatory requirements.
• Drive organizational change initiatives related to PMO process, tooling, and data adoption, ensuring proper documentation, communication, and training for teams and stakeholders.

Senior Director, Project Management Office

Business Development Rep

• Develop, build and implement the growth strategy for digital health ecosystem.
• Collaborate with top leadership across the company to align and implement a multi-pronged go-to-market strategy
• Partner closely with product teams to develop and package healthcare specific solutions.
• Develop a successful partnership with digital health platform and organizations for mutual performance objectives, targets, and breakthroughs associated with a successful relationship.
• Lead and support sales execution in partnership with our regional sales teams.
• Discover, develop, and nurture key customers relationships/Light House Accounts.
• Engage, enable, and energize channel sales teams including global system integrators, public cloud service providers to deliver joint go-to-market initiatives in a win-win-win situation
• Support sales critical issues, partner/channel dynamics and related business issues.
• Drive and track 4 quarters business on assigned responsibility.

Global Head of Business Development, Digital Health

Artificial Intelligence

• Primary responsibilities will include deploying, managing, and validating AI Compute/HPC infrastructure in Linux-based environments for new and existing customers.
• Be the domain expert with customers during planning calls through implementation.
• Handover-related documentation and perform knowledge transfers required to support customers as they begin rolling out some of the most sophisticated systems in the world!
• Provide feedback to internal teams such as opening bugs, documenting workarounds, and suggesting improvements.

Senior AI Compute Engineer - NVIS

• Engage with cross-company partners to shape the technical strategy, build and decom programs
• Nurture a culture of continuous improvement, finding new opportunities across tooling, automation and processes
• Guide a diverse set of engineering efforts in an agile program methodology
• Bring a data-first approach to programs to effectively measure success
• Act as an effective technical and non-technical liaison between developers, customers and partners

Senior Technical Program Manager – EDA Cluster Builds, Decoms

• Participate in the full life-cycle of tool development, test, and deployment of web applications and services for test automation and chip verification.
• Develop and optimize real-time data processing pipelines using Kafka Streams, Apache Flink and Spark Streaming, ensuring high throughput, reliability, and low-latency performance.
• Collaborate closely with hardware engineering and chip verification teams to understand data requirements and deliver robust, scalable data solutions and UIs
• Establish optimal guidelines for streaming data architecture, schema management, data retention and platform observability (monitoring, logging, tracing).
• Build microservices and AI agents that are reliable, scalable, and maintainable.

Senior Full-stack Software Engineer – Verification Data Platform

• Design and implement changes in NVIDIA SW stack to improve system level resiliency and reliability at datacenter scale with thousands of GPUs.
• Focusing on adding features that bolster system level availability, early fault detection and faster recovery.
• Follow the devices all the way through the development process to datacenter systems, customer desktops, notebooks, workstations, and gaming console products.
• Be heavily involved in architecture definition and early modeling, simulation required to create groundbreaking products.
• Multiple opportunities to collaborate and communicate effectively with teams from all around the globe.

Systems Software Engineer – GPU

• Lead and drive rack-scale/L11 flows for factory and initial data center deployment.
• Design and implement end-to-end factory workflows, including firmware flashing sequences, security provisioning, and deployment of software mitigations.
• Collaborate with data center architects, ODMs, and OEMs to define factory and data center requirements that ensure efficient and reliable production ramp.
• Champion reliability, debuggability and optimization in firmware, diagnostic and deployment tool design.
• Drive pre-silicon readiness for factory & manufacturing workflows for rack-scale products.
• Mentor architects and engineering teams to grow them into future leaders.
• Make key technical decisions even when faced with ambiguity.

Principal Software Engineer – Manufacturing, Factory

Designer

• Develop innovative HW, GPU and system designs to extend performance and efficiency.
• Drive Performance, Power and Area (PPA) improvements.
• Deliver fully verified, high performance, area and power efficient RTL.
• Collaborate with architects, designers, verification and VLSI teams.

ASIC Design Efficiency Engineer

• Be responsible for maintaining and improving mission critical infrastructure and test content
• Investigate failures and anomalies in automated build and test systems and drive to resolution with a team of experts
• Identify systemic problems in reporting systems, distill those into actionable investigations and drive service level improvements
• Write, configure and debug automated tests for system-level/kernel-mode software under Linux and Windows
• Architect new tools and refine processes that deliver productivity improvements

Senior Systems Integration Engineer

Engineer

• Develop automated CI/CD, BSP integration, and triage tools to accelerate issue detection, isolation, and regression tracking.
• Perform system bring-up, enable debug paths, and ensure platform integration readiness for NVIDIA reference and OEM partners.
• Integrate OEM and partner software into the NVIDIA software stack to ensure compliance, stability, and power/performance benchmarks for production platforms.
• Work closely with multi-functional teams to prioritize issues across all BSP components—firmware, drivers, kernel, and hardware layers.
• Collaborate with architecture, silicon, firmware, and OS engineering teams to enable new features and ensure seamless cross-component integration.

Senior Software Integration and Debug Engineer

AI Engineer

• Develop and implement solutions throughout software development lifecycles to improve developer efficiency, accelerate feedback loops, and boost release reliability.
• Experience designing, developing, and deploying AI agents to automate software development workflows and processes.
• Continuously measure and report on the impact of AI interventions, showing progress in metrics such as cycle time, change failure rate, and mean time to recovery (MTTR).
• Build and deploy predictive models to identify high-risk commits, forecast potential build failures, and flag changes that have a high probability of failures.
• Research emerging AI technologies and engineering best practices to continuously evolve our development ecosystem and maintain a competitive edge.