Top Tech Jobs & Startup Jobs

Define next-generation data center GPU products by analyzing workloads, especially large language model training and inference. Identify customer opportunities, develop GPU value propositions and product proposals, and collaborate with engineering, operations, field teams, cloud partners, and sales on go-to-market plans, positioning, collateral, and tools. The role requires technical knowledge of GPU, software, and computing architectures, along with 7+ years of technology experience.

Design, implement, and improve NVIDIA’s CUDA Driver and programming models, including CUDA Graphs and GPU kernel scheduling for AI/ML workloads. Lead cross-team development, define CUDA API improvements, develop well-tested code across operating systems, and address system-level challenges involving operating systems, memory, threads, and GPU architecture.

Lead architecture and development of Vehicle and Sensor Abstraction Layers (VAL/SAL) for autonomous vehicles. Manage teams building low-latency C++ systems with GPGPU (CUDA) acceleration, interfacing sensors and actuators, ensuring scalable integration, safety-compliant automotive software (MISRA), and validating via real-world and synthetic testing. Oversee in-vehicle tests, data analysis, unit testing, documentation, and cross-functional collaboration to deliver production-quality autonomy software.

Architect and develop scalable SaaS, web APIs, SDKs, CLIs, and AI-assisted developer tools for coding, debugging, profiling, and CUDA optimization. Collaborate with Product, Design, and engineering teams to define features, improve cloud infrastructure, and deliver reliable services for concurrent developers. Mentor engineers and review code and designs while applying Kubernetes, AWS, infrastructure as code, DevOps, Python, virtualization, and GPU profiling expertise.

Design, build, deploy, and operate cloud infrastructure and scalable I/O systems for scientific computing, physics simulations, AI workflows, and data-intensive workloads. Optimize compute, storage, and network architectures across CPU and GPU environments. Develop algorithms, debug systems and third-party code, and improve performance across distributed systems, operating systems, kernels, compilers, and parallel-processing frameworks while collaborating independently across teams.

Develops EDA software tools supporting PCB electrical design, physical layout, and signal integrity capabilities. Assesses system designer requirements, builds innovative CAD solutions, and improves development processes within an Agile team. The role requires experience with Cadence System Capture, Allegro Layout, CAD-level programming, system design, operating-system automation, databases, Python, and TCL. Preferred experience includes Cadence TCL APIs, software collaboration tools, PLM systems, and modern web technologies.

Design, deploy, and optimize on-premises HPC storage infrastructure integrated with cloud environments. Build automation, monitoring, alerting, and self-service tools for large-scale distributed storage systems. Manage enterprise NAS, S3, and parallel filesystems; evaluate technologies; resolve performance bottlenecks; document procedures; and collaborate with engineering teams on infrastructure requirements, application deployment, and resource utilization.

Leads portfolio-level strategy and operations for NVIDIA’s third-party events program. Oversees annual planning across business units, delivers 3–4 high-visibility events from strategy through follow-up, manages agencies and vendors, coordinates cross-functional teams, and advises senior executives. Owns team operating rhythms, executive reporting, special projects, partnerships, and initiatives that improve event programming and organizational effectiveness.

Develop and architect scalable Salesforce CPQ and Quote-to-Cash solutions. Translate business requirements into technical designs, implement integrations and ETL using APIs and Salesforce tools, provide platform support, write tests, optimize code, document solutions, and mentor developers. The role requires extensive Salesforce CPQ expertise, including complex pricing, product configuration, subscriptions, renewals, amendments, approvals, and migrations to Revenue Cloud Advanced.

Design and productionize machine learning solutions that predict and optimize GPU-accelerated Apache Spark workloads. Develop adaptive ML systems, AI agents, and optimization tools; collaborate with customers and partners on complex deployments; track advances in ML systems; and mentor engineers in data science and machine learning. The role requires expertise in large-scale data processing, modern ML/DL methods, LLMs, generative AI, reinforcement learning, online learning, feature engineering, and boosted-tree models.