Top Tech Jobs & Startup Jobs

Perform hands-on system, board, and component-level troubleshooting and failure analysis; drive root-cause to silicon/PCB/component; remotely diagnose deployed systems using Linux and telemetry; document findings and recommend corrective actions; collaborate with ASIC, systems, manufacturing, and vendors; contribute DFT and mechanical/thermal improvements for next-gen systems.

Build and evolve the Cerebras Developer Console: implement frontend (Next.js/TypeScript) and backend (GraphQL, Postgres, Redis) systems for usage tracking, billing, quotas, observability, and metrics. Make architectural decisions, drive projects from idea to production, and partner with product and design to shape developer workflows.

Design, build, and operate secure, scalable cloud infrastructure and identity platforms across AWS and data centers. Implement IAM/IGA, SSO/MFA, federation protocols, secrets and key management, and Zero Trust controls. Automate with Terraform, Python, and Go, deploy on Kubernetes, participate in on-call and incident response, and collaborate with Security and Engineering to deliver secure-by-design systems.

Lead end-to-end PCB design: define electrical specs, create schematics, select components, and oversee layout, bring-up, qualification, and production release. Perform extensive lab bring-up and automated benchtop debugging, develop test scripts, and collaborate with manufacturing, ASIC, signal integrity, power, embedded, mechanical, and supply chain teams.

Integrate, validate, and productionize cross-stack inference features across AI frameworks, runtime, compiler, kernels, distributed systems, and hardware. Drive zero-to-one projects, debug system-wide failures, manage accelerated timelines, and improve automation, diagnostics, and repeatable integration practices while collaborating across software and hardware teams.

Design and validate front-end datacenter and interconnect network fabrics for AI/HPC clusters. Lead multi-team projects, debug distributed networking issues, optimize performance, collaborate with vendors, shape hardware/feature roadmaps, and serve as the central contact for network reliability and industry representation.

Support system-level bring-up to configure, test, and validate systems before shipment. Collaborate with ASIC, software, diagnostics, and QA teams to automate and streamline workflows. Troubleshoot cross-domain issues, design tracking processes, report bring-up metrics, and implement software automation to scale manufacturing bring-up operations.

Develop and deploy large-scale deep learning models and LLMs for customers on Cerebras hardware. Scope projects, design training recipes (pretraining, SFT, RLHF/DPO), manage data pipelines, scale distributed training, analyze convergence/loss dynamics, build agentic systems, and serve as technical customer lead.

Lead a hands-on engineering team to improve kernel-centric reliability of large AI compute clusters. Own technical vision, build diagnostic and debug tooling, collaborate with SW and HW teams to reduce downtime, speed failure analysis, and mentor engineers to deliver scalable, reliable production systems.

Implement, optimize, and validate high-performance machine learning and linear algebra kernels for the Cerebras Wafer-Scale Engine. Develop low-level kernel routines using the Cerebras Software Language and C++, apply parallel programming techniques, profile and tune performance, debug correctness and hardware utilization issues, build tests and validation, and collaborate with compiler, performance, and hardware engineers.