Top Tech Jobs & Startup Jobs

Own end-to-end silicon program activities including specification, technology/IP selection, architecture tradeoffs, hardware-software co-design, and first-silicon bring-up/debug. Partner with external ASIC/IP/foundry partners, build AI-assisted design workflows, and drive directional technical decisions across chip domains from front-end to packaging and test.

Lead operations for high-visibility communications programs, turning ambiguous, fast-moving projects into clear workstreams, owners, timelines, and decisions. Drive alignment across cross-functional partners, design and improve playbooks and crisis protocols, anticipate and remove bottlenecks, and provide strategic program leadership for launches and reactive situations.

Build, maintain, and improve algorithms and infrastructure for finetuning and RL training (RLHF) of large language models. Improve speed, reliability, and usability of training pipelines through profiling, instrumentation, debugging GIL contention, launching test jobs, and implementing research algorithms to support production and internal model training.

Lead system-level architecture for large-scale AI compute: define specs, evaluate vendor designs, drive interconnect, power, thermal, and reliability strategies, develop validation and bring-up plans, and partner with ML, infrastructure, and supply chain teams.

The ML Infrastructure Engineer will develop and scale AI safety systems infrastructure, optimize machine learning pipelines, and ensure reliable system performance while collaborating with research teams.

Design and build real-time risk decisioning and tooling to prevent payments fraud. Implement fraud signals at scale, manage dispute and chargeback workflows, monitor metrics (loss, dispute, approval, false positives), lead investigations into emerging fraud patterns, and collaborate cross-functionally with finance, support, legal, data science, and external payment partners.

Build and maintain the shared web platform for Claude.ai: shared UI components, BFF APIs, build/deploy pipelines, and observability. Improve developer velocity, performance, reliability, and documentation to enable other product teams to ship quickly and reliably.

The Research Engineer will enhance RL training infrastructure, streamline research processes, and collaborate with teams to improve model deployment efficiency.

Build and productionize threat discovery infrastructure: ingestion pipelines, automated detection systems, YARA rule tooling, external CTI integrations, behavioral analytics, and investigator-facing tooling to scale investigations and reduce false positives.

Join the Web Product team to develop features for Claude.ai, transform user interaction, and enhance AI collaboration. Full-stack work across frontend and backend.