Top Tech Jobs & Startup Jobs

Design, develop, and optimize a low-latency, high-quality media streaming stack for cloud gaming. Analyze GPU/CPU video pipelines, isolate bottlenecks, collaborate with hardware teams, build tools to measure video quality, and implement adaptive streaming and codec-based improvements for resilient performance under variable networks.

The role involves researching and developing GPU-accelerated AI workloads, optimizing algorithms, and collaborating with technical experts to improve hardware performance.

Analyze GPU application performance and design, implement, and integrate MLIR/LLVM compiler optimizations and passes. Collaborate with hardware, compiler, and application teams, engage with open-source LLVM community, and enable best-in-class performance for AI and HPC workloads.

Join the Compute Compiler Team to align NVIDIA's compiler codebases with open-source projects (LLVM/Clang/MLIR), build tooling and workflows for large-scale codebase reconciliation, and develop automation and AI-assisted developer tools to improve productivity, validation, and refactoring across distributed teams.

Build and enhance NVIDIA Marketplace frontend experiences (product discovery, checkout, subscriptions, order management). Implement scalable React/Next.js/TypeScript applications in a monorepo, integrate with REST APIs, deliver features from design to production, and contribute to architecture, performance, accessibility, security, and developer productivity.

Develop and optimize an ultra-low-latency media streaming stack for GeForce NOW. Own end-to-end feature development, build tools for video performance and quality analysis, define metrics, analyze CPU/GPU utilization, improve network resilience, participate in design/code reviews, and advance team processes to meet performance, reliability, and scalability goals.

Lead a team to optimize algorithms for Deep Learning and Machine Learning, define technical initiatives, and collaborate with various teams for hardware and software innovation.

Design, implement, and productionize state-of-the-art deep learning and computer vision models for autonomous vehicles. Define and collect training datasets, build training pipelines and real-time inference runtimes, collaborate with researchers to turn experiments into robust, deployable systems, and optimize architectures for multi-sensor fusion and efficient deployment.

Lead architecture, implementation, and operation of highly available enterprise messaging and collaboration platforms (Exchange on-prem/hybrid/Online, SMTP/IMAP, Azure). Manage upgrades, patching, monitoring, security (SPF/DKIM/DMARC, anti-spam), migrations/tenant consolidations, and SaaS collaboration platforms. Provide incident diagnosis, mentor engineers, and drive automation and AI-enabled operational improvements.

Plan and execute performance benchmarks for DL and HPC frameworks, automate tests with Python, analyze and report results, debug performance issues, and improve tools/processes for automated testing across GPU-enabled applications and clusters.