Top Tech Jobs & Startup Jobs

Lead end-to-end bring-up of ML frameworks and models on Cerebras CSX systems, spanning model translation, compiler lowering, runtime integration, debugging performance/numerical issues, and prototyping tooling or API improvements to accelerate future deployments.

Lead testing strategy and execution for ML API features, building scalable test frameworks and automation to validate accuracy, fairness, and performance of inference systems. Drive pre-deployment and production validation across distributed cloud, multi-region, and hardware-backed inference environments. Mentor SDETs, champion best practices, debug complex distributed issues, and lead cross-functional quality initiatives to improve test coverage and engineering efficiency.

New graduate software engineer working on low-level, performance-oriented software for AI accelerator systems. Design, implement, test, and debug hardware-near components, support system bring-up, performance optimization, tooling, and cross-functional collaboration with hardware, firmware, compiler, and infrastructure teams.

Design, deploy, and maintain Linux servers and high-speed LAN/WAN networking across manufacturing sites. Implement automation (Ansible, Terraform), manage Palo Alto security, core switching (Arista/Juniper/Cisco), Wi‑Fi and ruggedized hardware, ensure redundancy/QoS, monitor performance, provide Tier 2/3 support and on‑call response, and lead IT/OT modernization and documentation efforts.

Design, deploy, and maintain global WAN connectivity across leased lines and dark fiber. Collaborate with carriers, configure and troubleshoot routing and security (BGP, IPSec, MACsec, VXLAN/EVPN), implement redundancy/QoS, monitor performance, support cloud connectivity (AWS/Azure/GCP), provide Tier 3 incident response, and automate network configuration with Python, Ansible, or Terraform.

Build and run operational analytics, KPI architectures, dashboards, and closed-loop processes across supply chain, manufacturing, and data center deployment. Partner with operations leaders to diagnose bottlenecks, redesign processes, automate reporting, run operating cadence, and deliver executive-ready insights that drive measurable operational improvements.

Entry-level engineer working at the software/hardware interface: kernel development, ASIC performance modeling, system bringup, performance profiling and debugging. Learn Cerebras Wafer Scale Engine end-to-end, model and tune performance, and validate designs on hardware and simulators using C++ and Python.

Adapt and optimize transformer-based language and vision models to run on Cerebras hardware. Design, prototype, and validate inference techniques (speculative decoding, pruning, sparse attention). Run experiments, profile performance, debug models, and collaborate with ML, software, and hardware teams to deploy low-latency, high-throughput inference solutions.

Lead architecture and roadmap for an end-to-end manufacturing test software platform spanning cloud and on-site client-server systems. Manage and mentor a full-stack engineering team, make cross-stack architectural decisions, drive integrations with hardware, data, and operations, and improve manufacturing efficiency through tooling, automation, and data infrastructure.

Drive end-to-end ML inference performance by building kernel- and system-level performance models, optimizing kernel microcode and compiler algorithms, debugging runtime and cluster performance, and developing tools to visualize performance data from the Wafer Scale Engine and compute cluster.