Top Tech Jobs & Startup Jobs

Design and analyze compensation programs, build analytic models and dashboards, automate reporting, support Workday compensation modules, conduct global market benchmarking, and communicate data-driven recommendations to stakeholders.

Design, develop, and optimize high-performance C++ systems for ultra-low-latency media streaming. Build and improve streaming pipelines (WebRTC, GStreamer, RTP/RTCP), analyze performance across server, network, and media pipelines, and collaborate with encoding, cloud networking, and systems teams to define KPIs and reduce latency for cloud gaming and related use cases.

Lead and grow a team building NvStreams/NvSci communication infrastructure for NVIDIA DRIVE OS. Drive embedded software development, ensure high quality and reliable schedules, collaborate cross-functionally, mentor engineers, and align technology with company goals.

Develop and execute product-level reliability qualification plans for advanced-node ICs and packaged devices. Collaborate with design, packaging, test, and product teams to validate reliability stress tests, analyze failures and failure mechanisms, build failure models, drive corrective actions, maintain reliability databases, and produce qualification reports and presentations.

Design and micro-architect a high-performance MMU for GPUs; develop and apply advanced verification methodologies; make architecture decisions; mentor engineers; collaborate with architects, designers, and software engineers across sites.

Design and implement Rust-to-GPU compiler backends, IR frameworks, and JIT/AOT toolchains. Lower Rust AST/MIR to MLIR/LLVM/PTX, build GPU-specific optimizers, enforce safe parallel abstractions across host/device boundaries, and expose ergonomic device-side primitives. Drive projects from research to production and support profiling, debugging, and benchmarking workflows.

Design, develop, and debug system software for NVIDIA Halos across QNX, Linux, and hypervisor environments. Build BSP, boot, drivers, device-management, and I/O virtualization for NVIDIA SoCs. Use formal methods and AI-assisted tools to develop safety- and security-compliant software (ISO 26262/21434). Perform platform bring-up, performance analysis, debugging, and cross-team integration for mixed-criticality, real-time embedded systems.

Enable end-to-end agentic AI GPU deployments on NVIDIA RTX and DGX by profiling and optimizing performance, contributing to open-source LLM/GenAI projects, delivering trainings and sample code, collaborating with drivers/architecture teams, and mentoring junior engineers.

Stabilize and optimize customer AI/HPC clusters post-deployment, address networking change requests, validate and troubleshoot InfiniBand/Ethernet fabrics, collaborate with CBU DevOps and Infrastructure Solutions Architects, and support pre- and post-sales networking engagements to help customers expand clusters.

Architect, prototype, and deploy production-grade agentic and multi-agent AI systems for Media & Entertainment. Build high-performance RAG pipelines over multi-modal assets, optimize GPU inference and TCO on NVIDIA platforms, advise customers pre/post-sale, and create reusable reference architectures, blueprints, and technical collateral to scale solutions.