Top Tech Jobs & Startup Jobs

Design, build, deploy, and operate large-scale GPU cloud infrastructure and tooling for AI training and inference. Perform performance analysis, capacity management, monitoring, automation, incident response, and lifecycle support for distributed multi-GPU/multi-node systems.

Lead research on human-AI perception and interaction: propose and prototype ideas, publish and patent results, build interactive demos, collaborate with engineers and external researchers, mentor interns, and transition research into products.

The role involves building and maintaining a workflow platform for chip engineering, focusing on automation, configuration systems, and debugging in a Linux environment. Responsibilities include managing workflows, improving diagnostics, and integrating job execution systems.

Implement and deliver high-performance, area- and power-efficient RTL for GPU/SoC IP. Analyze micro-architecture trade-offs, craft RTL, verify designs, and collaborate with verification, synthesis, timing, and back-end teams. Work on GPU scheduler, interrupt controllers, DMA, and support silicon debug and post-silicon validation.

Verify processor and accelerator designs using formal methods: write assumptions, assertions, and cover properties; debug counterexamples and RTL issues; use abstraction, modeling, and scripting to improve proofs; communicate verification progress, coverage, risks, and findings while collaborating with architects and RTL designers.

Design and implement high-performance Vision AI pipelines and large-scale distributed services for processing video, image, and 3D data across edge and cloud. Build multi-modal perception, use simulation/synthetic data for testing, profile and optimize GPU-accelerated inference, collaborate with research and product teams, drive code quality and reviews, and mentor engineers to productionize vision models at scale.

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

As an EDA Workflow Optimization Engineer, you will optimize and enhance workflows for chip development, working with teams to investigate, debug, and innovate tools for efficient engineering processes.

Lead the design and implementation of a GPU-accelerated propagation engine for predicting radio signal travel in 3D environments. Focus on real-time ray-tracing for 5G and 6G network simulation, optimizing for effective channel characterizations and rapid updates.

The Senior Silicon Product Development Engineer will oversee product development from pre-Silicon to market launch, manage project plans, maintain vendor relationships, and enhance manufacturing yields.