Lead the engineering organization responsible for defining, building, and delivering complex data and AI infrastructure software.
Compensation
The target salary range for this position is 266,050 - 396,000 USD.
Responsibilities
Own end-to-end engineering delivery, from design through implementation, testing, and production reliability.
Provide deep technical leadership, design reviews, and guidance on performance, scalability, security, and system tradeoffs, including accelerated computing where relevant; partner with senior architects to turn technical direction into robust products.
Translate product priorities and customer commitments into realistic engineering plans with clear owners, milestones, dependencies, quality gates, and measurable outcomes.
Build a disciplined execution culture with high engineering velocity, transparent progress, timely decisions, and accountability for commitments.
Recruit, coach, and retain exceptional engineers and engineering leaders; define team structures, clarify decision rights, develop successors, and raise the technical bar.
Lead the engineering organization responsible for defining, building, and delivering complex data and AI infrastructure software.
Compensation
The target salary range for this position is 266,050 - 396,000 USD.
Responsibilities
Own end-to-end engineering delivery, from design through implementation, testing, and production reliability.
Provide deep technical leadership, design reviews, and guidance on performance, scalability, security, and system tradeoffs.
Translate product priorities and customer commitments into realistic engineering plans with clear owners, milestones, dependencies, quality gates, and measurable outcomes.
Build a disciplined execution culture with high engineering velocity, transparent progress, timely decisions, and accountability for commitments.
Recruit, coach, and retain exceptional engineers and engineering leaders; define team structures, clarify decision rights, develop successors, and raise the technical bar.
Research & Engineering Intern on NVIDIA’s Agentic Systems Intelligence team, advancing high-performance AI systems across the CUDA ecosystem.
Compensation
Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The expected hourly rate for this position is 20 USD – 94 USD.
Responsibilities
Research, build, and optimize agentic AI systems for the CUDA ecosystem, including agent architectures, multi-agent workflows, tool use, memory, and orchestration.
Develop data pipelines, environments, verification tools, reward mechanisms, and evaluation frameworks to improve model and agent capabilities through rigorous experimentation.
Co-design and optimize agentic systems across NVIDIA’s software and hardware stack, connecting advances in models and agents with compilers, runtimes, libraries, kernels, and GPUs. Demonstrate measurable improvements in correctness, performance, or developer productivity.
Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The expected hourly rate for this position is 20 USD – 94 USD.
Responsibilities
Research, build, and optimize agentic AI systems for the CUDA ecosystem, including agent architectures, multi-agent workflows, tool use, memory, and orchestration.
Develop data pipelines, environments, verification tools, reward mechanisms, and evaluation frameworks to improve model and agent capabilities through rigorous experimentation.
Co-design and optimize agentic systems across NVIDIA’s software and hardware stack, connecting advances in models and agents with compilers, runtimes, libraries, kernels, and GPUs. Demonstrate measurable improvements in correctness, performance, or developer productivity.
Requirements
Master’s, or PhD in Computer Science, Electrical Engineering, or a similar field.
Nice to have: PhD research in a relevant area
Nice to have: building coding agents
Nice to have: autonomous software-engineering systems
Nice to have: agent training and evaluation environments
Lead and grow NVIDIA’s AI physics products, defining strategy, positioning, and go‑to‑market plans across key industries.
Compensation
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 168,000 USD – 258,750 USD for Level 4; and 208,000 USD – 327,750 USD for Level 5.
Responsibilities
Define and position AI physics products
Build strategic go‑to‑market plans
Execute product definition with engineering, developer relations, and business development
Present to external and internal audiences
Collaborate with marketing, sales, and PR teams on content creation
Requirements
Graduate degree in AI, physics, mathematics, mechanical engineering, electrical engineering, computer engineering, or equivalent
Lead the design and architecture of networking software for NVIDIA’s AI and data‑center infrastructure, integrating NICs, GPUs, and network management into high‑performance solutions.
Compensation
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
Responsibilities
Define and take responsibility for the complete platform architecture covering NICs and network management for computing clusters and data‑centers.
Drive the strategic vision for coordinated platform solutions addressing AI training/inference and cloud‑native workloads.
Lead cross‑functional collaboration with GPU, NIC, DPU, and network management groups to ensure seamless hardware‑software co‑design.
Define platform‑level software stacks, APIs, and management frameworks that orchestrate networking, compute, and acceleration resources.
Conduct and lead research into emerging network technologies, GPU‑networking convergence, and large‑scale cluster management.
Requirements
B.Sc. or M.Sc. in Computer Engineering, Computer Science, or Electrical Engineering or equivalent experience
Nice to have: network management and orchestration frameworks such as UFM, DOCA, or Kubernetes networking
Nice to have: defining platform standards or reference architectures
Lead the design and architecture of NVIDIA’s networking software stack for AI and data‑center infrastructure.
Compensation
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are: 184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
Responsibilities
Define and take responsibility for the complete platform architecture covering NICs and network management for computing clusters and data‑centers.
Drive the strategic vision for coordinated platform solutions addressing AI training/inference and cloud‑native workloads.
Lead cross‑functional collaboration with GPU, NIC, DPU, and network management groups to ensure seamless hardware‑software co‑design.
Define platform‑level software stacks, APIs, and management frameworks that orchestrate networking, compute, and acceleration resources.
Conduct and lead research into emerging network technologies, GPU‑networking convergence, and large‑scale cluster management.
Requirements
B.Sc. or M.Sc. in Computer Engineering, Computer Science, or Electrical Engineering or equivalent experience
Lead RF Data Scientist responsible for developing RF statistical‑learning techniques, leading experiments, and translating results into operational capabilities.
Locations (3)
Clarksburg, Maryland, United States
Arlington, Virginia, United States
Durham, North Carolina, United States
Compensation
US Salary Range $175,000—$220,000
Responsibilities
Lead RF technique development for detection, classification, parameter estimation, and complex signal environment understanding
Define technique inputs, targets, loss functions, uncertainty outputs, and decision rules for real RF collections
Build disciplined data practice including versioned datasets, label quality rules, leakage checks, and reproducible training and evaluation recipes
Developer Pulse Programming Clinical MRIPhilips · Best, Netherlands
Sr Director, Software EngineerNetApp, Inc. · San Jose, US
Lead RF Data ScientistForterra · Clarksburg, US+2 more
ML Systems, LLM Post-TrainingChipAgents · San Jose, US