Top Tech Jobs & Startup Jobs

Owns architecture, microarchitecture, RTL design, integration, and implementation of high-speed I/O and memory subsystems for AI accelerator platforms. Responsibilities include SystemVerilog development, front-end design flows, protocol and vendor IP integration, PPA optimization, timing closure, verification collaboration, issue resolution, and cross-functional lifecycle execution from architecture through silicon.

Leads ecosystem strategy for SambaNova’s AI accelerator products across networking, inference serving, storage, caching, prefill, CPU offload, and compiler systems. Defines build-versus-partner decisions, owns reference architectures and certification programs, drives co-optimization with software and model partners, and converts ecosystem relationships into deployments, demand, and revenue. The role also leads external positioning, analyst engagement, executive scorecards, and cross-functional execution with engineering, product strategy, marketing, and partners.

Leads competitive intelligence and product strategy for AI accelerator infrastructure. Builds TCO, tokenomics, capacity, and demand models; tracks competitor architectures, roadmaps, supply signals, and data-center systems; translates findings into roadmap, pricing, positioning, and investment decisions. Develops agentic AI tooling to automate research monitoring, specification extraction, and executive briefings. Runs weekly, monthly, and quarterly intelligence cadences for product and executive stakeholders.

Drive planning and execution of multiple software and ML workstreams, manage cross-functional dependencies, gather requirements, track schedules, support development-to-deployment, and improve processes to deliver customer product releases.

Develop and enhance runtime stack features for high performance ML applications, manage system software, and collaborate with teams to optimize AI systems.

Lead development and optimization of the compiler stack for ML systems, collaborate across teams, integrate and deploy products, map ML operations to hardware, and drive compiler infrastructure innovation and performance debugging.

The role involves leading a software engineering team focused on AI infrastructure and enterprise software, ensuring technical quality and team development while also contributing as a hands-on engineer.

Own and operate a global AI inferencing platform: ensure uptime, low-latency performance, scalability and cost efficiency. Build monitoring, alerting, CI/CD, IaC, autoscaling, capacity planning, incident response, and participate in a shared on-call rotation to maintain 24/7 service reliability.

Designs end-to-end data center reference architectures integrating SambaNova hardware and networking. Supports customer deployments, business development, demonstrations, proofs of concept, technical project management, troubleshooting, training, and product feedback. Requires deep networking expertise, system-level knowledge spanning Linux, kernel drivers, PCIe, NICs, and hardware architecture, plus customer-facing presentation skills. Travel is required approximately 30% of the time.

Design and implement RTL components for AI accelerator ASICs from microarchitecture through tape-out and silicon bring-up. Responsibilities include writing and debugging SystemVerilog, optimizing power, performance, and area, supporting synthesis and timing closure, and applying lint, CDC, LEC, and assertion-based quality checks. The engineer collaborates with architecture, verification, and physical design teams while contributing to compute datapath, on-chip network, and memory subsystems.