Updated Jan 27, 2026 using last 90 days postings.
NVIDIA Corporation Hiring Trends – January 2026
NVIDIA is rapidly scaling its machine learning and AI engineering teams, focusing heavily on developing and optimizing AI frameworks, reinforcement learning libraries, and large-scale distributed training systems. Concurrently, the company is expanding its manufacturing and production planning capabilities, particularly in Hong Kong, to support fluctuating demand through detailed supply chain scheduling and SAP-based order management. Additionally, NVIDIA is investing in infrastructure and system test engineering across global hubs, emphasizing performance verification, hardware design validation, and compliance in automotive software, while also growing developer relations and startup engagement in key regions like the US, Japan, and the UK.
Note: These dashboards are not the source of truth. Job posting data can include duplicates and may double count roles. Treat the results as a sample that helps explain what the postings suggest about hiring focus. Summaries are generated with an LLM and may contain errors or omissions. For the most accurate and complete information, research the company directly.
Tracked openings
1,509
Remote share
1%
Top location
United StatesCA (705), TX (59)
Top category
Machine Learning And Ai Engineering
Inside The Product
SummaryNVIDIA is scaling both AI software and large-scale AI/HPC hardware delivery: job postings emphasize AI training/post‑training frameworks, developer tools, and deployment of GPU/HPC infrastructure alongside manufacturing, test, and verification for datacenter products. Roles span product strategy, developer relations, supply chain/production planning, and extensive hardware/software verification to support rapid engineering growth and productization.
What They Build
- AI frameworks and post‑training/RL libraries (GitHub‑first developer products for researchers and production model builders)
- Distributed training and optimization software for large‑scale model training and inference
- AI/HPC infrastructure and GPU cluster deployment and networking (InfiniBand/Ethernet) for datacenter customers
- Silicon/IP design and verification (PCIe, interconnects) and firmware performance testing for new architectures
- Manufacturing test solutions, production planning, and supply allocation across contract manufacturers and sites
- Developer and partner programs (ISV engagement, startup Inception) to drive adoption and integrations
Customers & Users
- Research teams and production model builders
- Independent software vendors (ISVs) and developer ecosystem
- Datacenter and HPC customers/operators
- Contract manufacturers, ODMs/CMs, and internal manufacturing stakeholders
- Startups in AI/compute ecosystems (NVIDIA Inception)
- Automotive engineering and safety teams requiring traceability/compliance
Workflows & Systems
- Product strategy and roadmap development for open‑source, GitHub‑first AI developer products with deep customer engagement
- Master production scheduling, SAP PO and supply‑order management, WIP re‑prioritization, and raw material allocation across sites
- Design, deploy, and maintain automated performance regression cycles and test infrastructure for firmware and system performance
- Define and deploy manufacturing test fixtures, rack‑level testers, and site test capacity at CMs/ODMs for datacenter products
- ASIC/IP verification workflows using UVM, constrained‑random/coverage‑driven methodologies and reusable bus models
- Deploy and optimize AI/HPC clusters with automation tooling (Ansible/Salt/etc.), networking tuning, and Linux systems administration
- Traceability, compliance, and release workflows aligned to ASPICE/ISO 26262 using ALM/PLM tools (Jama/DOORS/Jira)
Role Insights
Machine Learning And Ai Engineering
Hiring product and engineering talent to build and scale training/post‑training RL libraries and optimization frameworks (open‑source, GitHub‑first) for researchers and production model builders.
Hardware Design And Verification
Scaling verification teams to validate ASIC/IP and interconnect controllers (PCIe, USB, SATA) using UVM and coverage‑driven constrained‑random methodologies.
Embedded Software Engineering
Hiring firmware and automation engineers to create performance testing infrastructure, automate regression cycles, and validate data/control path performance for new interconnect/firmware features.
Robotics And Autonomous Systems
Recruiting for automotive and safety‑focused roles that own traceability, compliance artifacts, and ASPICE/ISO 26262 aligned test and reporting workflows.
Software Engineering
Building scalable software for performance verification, distributed systems, developer tooling, and production test automation across datacenter and product teams.
Software Engineering Leadership
Seeking leaders for cross‑functional programs (developer relations, product management, test engineering) to align roadmaps, partner integrations, and operational execution at scale.
Team Focus
- Machine Learning And Ai Engineering: 250 roles (16.6%)
- Hardware Design And Verification: 190 roles (12.6%)
- Embedded Software Engineering: 170 roles (11.3%)
- Robotics And Autonomous Systems: 122 roles (8.1%)
- Software Engineering: 103 roles (6.8%)
- Software Engineering Leadership: 69 roles (4.6%)
- Mechanical Engineering: 48 roles (3.2%)
- Engineering Management: 46 roles (3.0%)
Skill Stack
Machine Learning And AI Engineering
Hardware Design And Verification
Embedded Software Engineering
Robotics And Autonomous Systems
Software Engineering
Software Engineering Leadership
Location Footprint
- CA, US: 705 roles (46.7%)
- Israel: 154 roles (10.2%)
- China: 113 roles (7.5%)
- India: 94 roles (6.2%)
- Taiwan, Province of China: 84 roles (5.6%)
- TX, US: 59 roles (3.9%)
- WA, US: 42 roles (2.8%)
- United States, US: 33 roles (2.2%)
Seniority Mix
- Senior: 999 roles (66.2%)
- Mid: 383 roles (25.4%)
- Intern: 113 roles (7.5%)
- Entry: 14 roles (0.9%)
Role Types
- full_time: 1509 roles (100.0%)