Top Tech Jobs & Startup Jobs

Lead and mentor engineering teams in the JAX ecosystem, ensuring peak performance across NVIDIA hardware, and promote collaboration across departments to enhance AI platforms.

Lead and coordinate SAP BPC processes for headcount, OPEX, and CAPEX planning, govern cost center master data in SAP MDG, manage month-end close and data validations, support users and FP&A stakeholders, liaise with IT, drive continuous improvements, maintain SOPs and audit documentation, and lead/support UAT and system testing.

Lead architecture and specification of chip-to-chip interconnects (NVLink), collaborate with research, architects, and design teams, create architectural models and documentation, drive implementation across design/verification/firmware/software, and define NVLink fabric, network configuration, and management flows throughout product lifecycle.

Lead development of memory system architecture and micro-architecture for SoCs. Build and maintain performance models and simulations, analyze benchmarks and workloads, identify micro-architectural tradeoffs, and debug performance and functional issues across high-level models, RTL simulation, and silicon.

Lead architecture and development of next-generation scale-up fabrics and collaborative communication for AI data-centers. Ensure scalability, reliability, and robust large-model training across hardware, software, and applications while driving innovation and cross-functional implementation toward production and manufacturing.

Verify SoC/GPU designs using advanced verification methodologies. Define verification scope and infrastructure for memory subsystems, develop reusable verification components, collaborate with architects, designers, and software engineers, and debug complex issues.

Design and architect on-chip GPU/CPU clock domains, collaborate with front-end, physical design, timing, verification and SW teams to implement clock RTL, optimize PPA, support ASIC implementation through sign-off and silicon bring-up.

Drive end-to-end quality in AI microservices, lead testing strategies, mentor engineers, and enhance automation practices while validating AI inference workflows.

Lead performance practices for large-scale AI systems, enhance datacenter products, and resolve complex performance issues through collaboration and technical expertise.

Lead architecture, design, and development of hardware-accelerated AI networking software (BlueField DPU, ConnectX). Drive deep technical engagements with hyperscalers for design-in, bring-up, performance tuning, failure analysis, and production hardening. Partner cross-functionally to turn customer needs into product features, tooling, and roadmap items while improving performance, reliability, and debuggability across stacks.