Top Tech Jobs & Startup Jobs

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.

Leads go-to-market execution for hardware products from ideation through launch and sustaining. Coordinates hardware, software, marketing, operations, and JDM/ODM partners to meet schedule, scope, budget, quality, and delivery goals. Manages product risks, status communications, partner alignment, beta testing, customer feedback, and roadmap improvements. Requires engineering education, five or more years of experience, hands-on hardware product development, and strong product, program, and project management skills.

Leads North American logistics execution programs, optimizing transportation, packaging, equipment utilization, capacity, and service reliability. Manages 3PL and carrier performance, cross-functional initiatives, site and lane launches, TMS and ERP implementations, business continuity planning, and continuous improvement using Lean and Six Sigma. Develops logistics strategies, dashboards, KPIs, SOPs, and AI or automation capabilities while influencing suppliers and internal teams to improve delivery speed, quality, capacity, and cost.

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.

Leads a distributed team securing NVIDIA DGX Cloud’s large-scale GPU infrastructure. Responsibilities include hiring and developing engineers, setting strategy for security control planes and foundational services, delivering measurable risk reduction, maintaining engineering standards, communicating security risks to executives, and collaborating with platform, SRE, networking, and security teams. The role requires strong engineering management, infrastructure or security expertise, cloud-native fluency, and influence across partner organizations.

Drive adoption of NVIDIA Omniverse and physical AI technologies across software partners. Advise engineering teams on architecture, coding, integrations, and reference solutions; create technical enablement materials; lead workshops and technical engagements; resolve implementation blockers; communicate partner feedback internally; and support product launches and technical go-to-market activities. The role requires extensive software development experience, industrial or robotics technology expertise, and the ability to influence engineers, executives, and product teams.

Lead real and personal property tax compliance, filings, audits, assessments, appeals, forecasting, and reporting. Manage franchise tax, Form 720, and FBAR processes across corporate entities. Use SAP to maintain tax and fixed-asset data, improve processes, and support accurate reporting. Partner with finance, accounting, IT, consultants, assessors, and taxing authorities while monitoring regulatory changes and developing strategies to reduce tax liabilities.

Develop and deploy machine learning models, datasets, algorithms, and training recipes to improve AI safety for multimodal LLMs and agentic systems. Work across LLM security, frontier risks, agentic safety, multi-turn evaluation, content safety, hallucinations, and fairness. Apply post-training methods including SFT and RLHF/RLAIF, conduct safety evaluations and research, and collaborate cross-functionally with engineering, data science, and research teams.

Builds developer and customer relationships across the Jetson ecosystem, guides partners through embedded Linux and Jetson software integration, promotes NVIDIA AI libraries and edge AI capabilities, supports production deployments, and communicates developer feedback to engineering and product teams to shape platform roadmaps, reference designs, positioning, and adoption.