NVIDIA

Software Engineer

• Direct the product roadmap for AI features integrated within internal tools across the data center lifecycle (planning, procurement, deployment, operations, and decommissioning).
• Identify new opportunities to deploy AI solutions using existing data.
• Prioritize opportunities based on feasibility and impact.
• Assemble user requirements for features and improvements driven by artificial intelligence.
• Conduct discovery sessions with internal collaborators (data center engineers, operations leads, planning/procurement teams) to understand workflows, difficulties, and where AI can help or automate processes.
• Transform these insights into detailed product requirements and user stories, for AI features.
• Work closely with development and UX teams to guarantee AI functions are easily comprehended within existing internal tools and dashboards.
• Incorporate clear confidence indicators, explanations, and controls.
• Establish and sustain effective feedback channels with internal users.
• Identify user-facing controls and review procedures suitable for operational settings (e.g., suggestions needing human approval, override/rollback options, feedback on inaccurate recommendations).

Senior AI Product Manager – Data Center Engineering and Operations

Content Marketing Manager

• Own and improve OpenUSD-based content workflows for reusable technical assets, from intake and packaging through validation, publishing, and lifecycle updates.
• Define practical metadata, profile, and validation requirements for infrastructure, simulation, and digital twin assets.
• Partner with engineering, program, content, and contributor teams to improve packaging, versioning, publishing, and asset readiness patterns.
• Support internal teams and external contributors as they prepare, refine, and submit assets into structured workflows.
• Shape how approved assets appear across catalog, browser, and search surfaces so they are easier to find and reuse.
• Create workflow guidance, examples, and reusable technical content that makes participation repeatable and scalable.

Senior Content Workflow Specialist, Digital Twins

Account Manager

• Own account strategy, sales pipeline & forecasting, executive engagement, and business outcomes for a select portfolio of enterprise ISVs.
• Build positive relationships with C-level executives, product leaders, architects, developers, data scientists, IT leaders, and decision-makers.
• Accelerate ISV adoption of NVIDIA tools, SDKs, libraries, frameworks, models, blueprints/reference architectures, and AI acceleration technologies across ISV platforms.
• Translate NVIDIA platform capabilities into clear business value, differentiated partner solutions, and measurable revenue opportunities.
• Develop joint GTM plans with ISVs, hyper-scalers, OEMs, and ecosystem partners to promote and sell embedded NVIDIA-powered solutions.
• Collaborate with NVIDIA solution architects, engineering, product management, product marketing, business units, developer relations, and enterprise sales to remove barriers and scale impact.
• Evangelize the use of NVIDIA's platform, products, and technologies to your customers and partners.

Senior Account Manager, Enterprise ISVs

Architect

• Bridge the gap between architecture, RTL implementation, and physical design.
• Serve as subject matter expert on power delivery/regulators, power gating, di/dt, and thermal throttling.
• Analyze power trade-offs for different die stacking and packaging proposals.
• Propose and drive improvements related to power and power methodology for our custom CPU cores.

Principal CPU Power Architect

Full-stack Engineer

• Design and build performance analysis tools and workflows for AI training and inference workloads
• Understand how AI performance engineers work and translate their needs into scalable, intuitive tooling
• Develop integrations between profiling infrastructure and AI frameworks and workflows
• Collaborate with performance engineers, hardware architects, and software teams to ensure profiling capabilities align with real-world AI workloads
• Identify performance bottlenecks in AI workloads and develop automated approaches to detect and diagnose them

Senior Software Engineer, AI Performance Analysis

Engineer

• Invent and develop new algorithms for RTL synthesis, digital logic optimization, graph-based RTL traversal, analysis, and manipulation.
• Build physical-aware synthesis techniques using placement/congestion/timing feedback to improve PPA.
• Develop strategies for rapidly analyzing the RTL change impact on timing, power, area, and impact to DFT, clocking, and power delivery on design.
• Prototype and evaluate ML methods (e.g., GNNs, RL, models) to guide optimization decisions; integrate successful approaches into production.
• Explore high performance algorithms for clustering, min cost tree covering (technology mapping), datapath implementation and other details of logic synthesis, especially that efficiently incorporate human insight.
• As a team, own the whole process from discovery and invention of new optimization opportunities, to developing solutions and working directly inside design teams to facilitate deployment.

Software R&D Engineer, Digital Logic Synthesis

• Co-developing NIC software and communication paths with strategic, top-tier customers to enable and scale large AI superclusters.
• Designing and implementing high‑performance C/C++ components on Linux using DPDK, kernel-bypass techniques, and RDMA/RoCE.
• Developing and integrating kernel, driver, and NIC firmware features to improve throughput, latency, and reliability for AI workloads.
• Working closely with NCCL and distributed training teams to tune end-to-end collectives performance over NVIDIA networking at scale.
• Owning complex performance and functionality debug with customers and representing the team in cross-org architecture discussions.

Principal Software Engineer – Networking, Hyperscale Engineering

Solutions Engineer

• Guide customers through the end-to-end adoption of GPU-accelerated AI, from requirements gathering and proof-of-concept development to deployment, integration, and ongoing optimization.
• Architect libraries such as GPU-accelerated solvers for quantitative systems pharmacology and CPU-to-GPU migration of scientific workloads.
• Perform low-level CUDA optimization, including custom kernels to accelerate simulation and inference workloads in drug discovery.
• Building physical AI and robotics solutions for autonomous labs and biomanufacturing such as sim-to-real VLA pipelines, real-time control layers, and integration of perception, control, and policy stacks on NVIDIA platforms.
• Designing and deploying biomedical agentic AI systems, such as graph-based retrieval, multi-hop clinical reasoning, and persistent agent memory.
• Keeping up to date on AI advancements in healthcare, including domain-specific models, robotics, and agentic frameworks.
• Engaging with life science executives, IT leaders, data scientists, and developers to drive adoption of NVIDIA AI stack.
• Sharing findings through training sessions, white papers, blog posts, and conference talks.

Senior Solutions Architect – Simulations, Clinical Sciences, Autonomous Lab

• Partner with business and account teams to understand customer goals, scientific workflows, technical needs, and platform adoption strategies.
• Architect and optimize AI/ML pipelines for training large biological foundation models, with a focus on BioNeMo libraries and GPU-accelerated software that improve training efficiency.
• Build proof-of-concept demonstrations that show how NVIDIA software and hardware accelerate scientific discovery.
• Collaborate across NVIDIA with subject matter experts, engineering, product, and field teams to bring the right technical expertise to customer engagements and deliver high-impact solutions.
• Document best practices and teach others through technical enablement, partner training, whitepapers, blogs, internal wiki articles, and hands-on customer workshops.
• Serve as a trusted technical advisor for integrating NVIDIA technologies into advanced biopharma and diagnostics applications.

Senior Solutions Architect – Drug Discovery

Manager

• We partner with grid software providers, power systems ISVs, automation companies, global systems integrators, service delivery partners, cloud providers, and system OEMs to bring NVIDIA technology to the power industry.
• This role builds the business relationships, partner strategies, and joint go-to-market plans that help turn NVIDIA accelerated computing, AI, simulation, and digital twin platforms into scalable solutions for utilities, grid operators, power producers, and energy infrastructure companies.
• The work includes collaborating with partner leadership, NVIDIA Energy Solution Architects, field teams, and product teams to support PoCs, platform porting, solution development, RFQ responses, and customer pursuits.
• We focus on high-impact use cases across transmission planning, interconnection studies, distribution operations, grid simulation, outage management, asset optimization, demand flexibility, substation automation, and grid edge intelligence.

Global Energy Partner Ecosystem Manager

Influencer Marketing

• Research and vet prospective content creators on multiple social and digital video platforms to determine fit for active and planned marketing campaigns, including evaluating past performance and brand/game/product affinities
• Support the onboarding of new sponsored creators and agency partners by directing the flow of documentation related to vendor and activation management
• Undergird campaign activations by tracking candidates from evaluation through onboarding, collecting and distributing critical documents, capturing data, contributing to reports, and facilitating internal reviews and approvals
• Provide hands-on support and mentoring to influencers at one or more industry events where NVIDIA has a presence
• Perform administrative functions on NVIDIA’s influencer database solution and toolset
• Some domestic travel, funded by NVIDIA, may be required

Influencer Manager

Artificial Intelligence

• Direct a customer focused engineering team partnering with major clients and broad AI infrastructure efforts
• Lead, support, and grow a high-performing team of customer-facing networking engineers
• Provide organizational and technical leadership across NVIDIA networking technologies, including BlueField, ConnectX, Spectrum-X, DOCA, RDMA, RoCE, and InfiniBand
• Support large-scale customer design-in, bring-up, and deployment of current and next-generation AI systems
• Engage directly with engineering, product management, architecture, and program teams to translate field requirements into product improvements and roadmap priorities
• Build team capability through hiring, onboarding, coaching, mentoring, and performance management
• Develop future leaders by strengthening technical leadership and team ownership
• Guide resource planning and customer prioritization across multiple strategic accounts to enhance business impact and execution quality
• Improve team scalability by investing in debugging methods, telemetry, automation, documentation, and operational excellence

Senior Software Manager, AI Networking

• Create and integrate AI agents to enhance the efficiency, productivity, and quality of VLSI design flows
• Collaborate on the design and implementation of algorithms and models that can optimize VLSI design processes
• Contribute to the development of software tools and frameworks that support the integration of AI in VLSI design
• Analyze and interpret data to identify patterns and insights that can inform the development of AI-driven design methodologies
• Stay ahead of the latest advancements in machine learning, deep learning, and VLSI build to continuously improve our solutions

Senior System Software Engineer, AI for Chip Design

• Work towards building applications and developing infrastructure for a highly scalable deep learning platform
• Design, build, and maintain high bandwidth data-pipelines and related infrastructure, such as APIs, databases and services
• Work closely with domain experts, research teams and take ownership of productizing, releasing and maintaining deep learning products
• Be an engineering generalist
• Discover and build skills needed at different times towards solving problems at hand

Senior Systems Software Engineer, Deep Learning Infrastructure

• Lead the end-to-end delivery of high-quality software releases for host and switch products
• Collaborate with Engineering, Operations, Architecture, and Marketing
• Analyze release data, R&D feature status, and bug metrics
• Facilitate critical release milestones
• Manage simultaneous release tracks across various lifecycles
• Direct bug triage processes
• Monitor cross-team dependencies and escalate risks
• Oversee release branches, builds, and versioning